"Benifuuki" Extract Reduces Serum Levels of Lectin-Like Oxidized Low-Density Lipoprotein Receptor-1 Ligands Containing Apolipoprotein B: A Double-Blind Placebo-Controlled Randomized Trial.

Nutrients. 2018 Jul 19;10(7). pii: E924. doi: 10.3390/nu10070924. Miyawaki M1, Sano H2, Imbe H3, Fujisawa R4, Tanimoto K5, Terasaki J6, Maeda-Yamamoto M7, Tachibana H8, Hanafusa T9, Imagawa A10. Author information 1 Department of Internal Medicine (I), Osaka Medical College, 2-7 Daigaku-machi, Takatsuki 569-8686, Japan. in1295@osaka-med.ac.jp. 2 Department of Internal Medicine (I), Osaka Medical College, 2-7 Daigaku-machi, Takatsuki 569-8686, Japan. in1209@osaka-med.ac.jp. 3 Department of Internal Medicine (I), Osaka Medical College, 2-7 Daigaku-machi, Takatsuki 569-8686, Japan. in1297@osaka-med.ac.jp. 4 Department of Internal Medicine (I), Osaka Medical College, 2-7 Daigaku-machi, Takatsuki 569-8686, Japan. in1337@osaka-med.ac.jp. 5 Department of Internal Medicine (I), Osaka Medical College, 2-7 Daigaku-machi, Takatsuki 569-8686, Japan. in1120@osaka-med.ac.jp. 6 Department of Internal Medicine (I), Osaka Medical College, 2-7 Daigaku-machi, Takatsuki 569-8686, Japan. terasaki@osaka-med.ac.jp. 7 National Agriculture and Food Research Organization, Agri-Food Business Innovation Center, 3-1-1 Kannondai, Tsukuba 305-8517, Japan. marimy@affrc.go.jp. 8 Division of Applied Biological Chemistry, Department of Bioscience and Biotechnology, Faculty of Agriculture, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka 812-8581, Japan. tatibana@agr.kyushu-u.ac.jp. 9 Sakai City Medical Center, 1-1-1 Ebaraji-cho, Nishi-ku, Sakai 593-8304, Japan. hanafusa@sakai-hospital.jp. 10 Department of Internal Medicine (I), Osaka Medical College, 2-7 Daigaku-machi, Takatsuki 569-8686, Japan. imagawa@osaka-med.ac.jp. Abstract (1) Background: Arteriosclerosis is associated with high levels of low-density lipoprotein (LDL) cholesterol. O-methylated catechins in "Benifuuki" green tea are expected to reduce cholesterol levels, although there is limited research regarding this topic; (2) Methods: This trial evaluated 159 healthy volunteers who were randomized to receive ice cream containing a high-dose of "Benifuuki" extract including 676 mg of catechins (group H), a low-dose of "Benifuuki" extract including 322 mg of catechins (group L), or no "Benifuuki" extract (group C). Each group consumed ice cream (with or without extract) daily for 12 weeks, and their lipid-related parameters were compared; (3) Results: A significant reduction in the level of lectin-like oxidized LDL receptor-1 ligand containing ApoB (LAB) was detected in group H, compared to groups L and C. No significant differences between the three groups were detected in their levels of total cholesterol, triglycerides, and LDL cholesterol; (4) Conclusions: "Benifuuki" extract containing O-methylated catechins may help prevent arteriosclerosis. KEYWORDS: Benifuuki; LOX-1 ligand; Lectin-like oxidized LDL receptor-1; O-methylated catechin; dyslipidemia PMID: 30029523 PMCID: PMC6073342 DOI: 10.3390/nu10070924 [Indexed for MEDLINE] Free PMC Article

Two Randomised Clinical Trials on the Use of Bryophyllum pinnatum in Preterm Labour: Results after Early Discontinuation

https://www.karger.com/Article/Abstract/487431 Research Report · Forschungsbericht Simões-Wüst A.P.a · Lapaire O.b · Hösli I.b · Wächter R.a · Fürer K.a · Schnelle M.c · Mennet-von Eiff M.c · Seifert B.d · von Mandach U.a Author affiliations Keywords: Kalanchoe pinnataTocolysisNifedipinePreterm labourBryophyllum pinnatum Complement Med Res 2018;25:269-273 https://doi.org/10.1159/000487431

Professors are selling their plasma to pay bills. Let's hold colleges' feet to the fire

https://www.theguardian.com/inequality/2018/nov/27/professors-are-selling-their-plasma-to-pay-bills-lets-hold-colleges-feet-to-the-fire If you like your coffee fair trade, why not your children’s school ‘fair labor’? Here’s a simple but effective proposal Alissa Quart @lisquart Tue 27 Nov 2018 11.00 GMT Last modified on Tue 27 Nov 2018 11.02 GMT A 2015 survey by Pacific Standard found that 62% of adjuncts made less than $20,000 a year. Illustration: Rosie Roberts Former New York mayor Michael Bloomberg recently gave $1.8bn to his alma mater, Johns Hopkins University in Baltimore, Maryland, for financial aid. The donation, the biggest gift of its kind, will enable Johns Hopkins to ensure permanently need-blind admissions. Bloomberg’s big-ticket donation has received plenty of headlines – and criticism – for simply adding to the coffers of an already elite institution. To me, however, his donation highlights another problem involving money on campus that no philanthropist seems to want to touch: the sheer amount of terribly paid adjuncts now toiling away at American universities. Over the last few years, I have talked to numerous adjunct professors in extreme situations: homeless, living in their cars, getting their meals from their university’s food bank, taking extra jobs to support their families, even donating plasma. Top-tier American universities charge tens of thousands of dollars a year in tuition – yet they get away with exploiting legions of adjunct professors, underpaid and economically insecure, who work long hours and typically do not even receive health insurance. Many are living below the poverty line, while the colleges that employ them continue to operate with endowments in the many millions of dollars. A 2015 survey by Pacific Standard found that 62% of adjuncts made less than $20,000 a year. Knowing this, how can we, as students, parents and alumni, know if the institutions which happily accept our checks provide their staffs with even a bare minimum standard of living? Here’s an idea: a “fair labor” seal or rating for colleges and universities. (Ditto for elementary, middle and high schools, especially when they are private, charter or otherwise not unionized.) A fair labor label would affect colleges where they live: their public image. Ratings would be based on factors like what percentage of a college’s faculty is non-tenure-track. Currently, the ratio of full-time faculty on a given campus counts for only 1% of the criteria by which the US News & World Report ranks colleges. What if that percentage factor was more heavily weighted? After all, the Report’s rankings are considered the gold standard. And what if other variables were considered, such as how much a college pays its adjunct professors per course, whether casual workers can unionize and whether they have access to healthcare plans? Some naming-and-shaming is overdue – and probably highly effective. Universities such as Yale and Boston College, which have vigorously fought efforts by graduate student workers and adjuncts to unionize, would sweat for a fair labor seal. So would Vermont Law School which, in a move that would once have been inconceivable, recently revoked the tenure of 75% of its tenured faculty. Tenured Queens College literature professor Talia Schaffer is a board member of the group Tenure for the Common Good, an organization that describes itself as “seeking to rally tenured faculty to use their tenured positions to fight for justice”, working alongside non-tenured colleagues “to achieve the goal of equity in the academic workplace”. She put it bluntly. “If you have a child in college, she is likely being taught by someone being paid starvation wages,” says Schaffer. “Maybe they are homeless, with no medical care, no office, no supplies, no books, working around the clock just to make enough money to survive.” This is unacceptable. Colleges are fond of boasting of their Leed certifications, which are granted for meeting certain environmental standards for buildings. A fair labor seal could be an equivalent certification guaranteeing the wellbeing of the humans who work in those buildings. If created, the seal would quickly become a default standard in transparency and consumer choice – a trustworthy measure of good business practices much like the Leed certificate. That would empower students and parents as well as adjuncts and other non-tenured workers: perhaps all workers at a university, in fact. After all, we worry about the labor conditions of the farmers who grow our coffee and the factory workers who make our clothes. Why not our professors? Indeed, it’s hard to imagine how a fair labor seal wouldn’t appeal to the idealistic students and their parents that these schools want to attract. These students want to know their money is spent on ethically produced goods and services – that their food is organic and pasture-fed; that their shampoos are cruelty-free; that their mascara hasn’t been tested on rabbits. Consumers like this are the reason Starbucks and other purveyors of fine caffeine use fair trade logos to let us know that the people who picked our coffee beans are fairly compensated. A higher education fair labor seal would certainly appeal to the same demographic. It would also tear a label, so to speak, from previous labor movements. Think of the ILGWU tags that were for many years sewn into any piece of clothing made by the International Ladies Garment Workers Union, or the 1990s Clean Clothes Campaign against sweatshops. If we created a fair labor seal for colleges, it could worm its way into the US News & World Report’s rankings that spellbind so many college-bound teens and their parents. In fact, Schaffer told me that Tenure for the Common Good has met with Robert Morse, the head of the ranking team at US News & World Report, in the hopes of persuading the popular guide to hold colleges more accountable for their labor practices. Schaffer was inspired by the dismal situation in her own academic department – now 63% adjuncts, she says, “shouldering triple or quadruple the work”. As a former CUNY adjunct I shivered at these numbers. “Higher education in the US is getting destroyed by this system,” she said. A fair labor seal might also appeal to the self-interest of students and parents. Such a seal, Schaffer noted, could “help parents choose viable universities for their kids – universities where faculty have conditions that enable them to teach well”. What would happen, for instance, if we reminded parents that graduate student workers at ultra-rich schools had tried to form a union – and were told to take a hike by the university? (As of this week, Columbia University finally agreed, after much hectoring, to bargain with graduate workers, though generally graduate unions and adjunct unions are separate.) What would happen if more parents realized that the lavish cost of their children’s education goes to country club amenities – while the professors who actually teach their children are underpaid, miserable and struggling to pay off their own college loans? Some of this is branding. For a fair labor campaign to work, it needs an easy-to-grasp rating system and a recognizable logo. Eileen Boris, a professor of feminist studies at the University of California, Santa Barbara, reminded me of the popularity of the ILGWU’s “Look for the union label” jingle in the 1970s. I remember the earnest union label adorning many of the clothes I wore growing up. American labor today needs to re-adopt some of that liveliness and simplicity of expression. Language is key. Although American culture is known for its individualistic, free-market ethos, Americans also believe very earnestly in “fairness” as a value – and college labor practices are badly lacking in fairness. Finally, when I asked fellow parents whether they would factor in whether a fair labor seal was affixed to their children’s costly education, the answer was a resounding yes. The fair labor seal for higher education could easily gain momentum. If so, it might protect college freshmen from some pretty dark realizations. After all, discovering that your professor is dwelling in poverty is not the type of education any student wants.

False oil price narrative used to scare Canadians into accepting Trans Mountain pipeline expansion

https://www.nationalobserver.com/2018/11/26/analysis/false-oil-price-narrative-used-scare-canadians-accepting-trans-mountain-pipeline By Robyn Allan in Analysis, Energy | November 26th 2018 Alberta Premier Rachel Notley on Apr 15, 2018. Photo by Alex Tétrault Alberta Premier Rachel Notley is aggressively advancing a false narrative about heavy oil’s deep discount. She presents the problem in two parts, neither of which stand up to scrutiny. First, Notley purports that the abnormally wide price spread affects every barrel of heavy oil leading to millions of dollars a day in losses to the Canadian economy. And second, that the Trans Mountain pipeline expansion is crucial. Neither of these claims are supported by the facts. Most Alberta oil is sheltered from the price discount When you crunch the numbers, and include the variety of methods even the smaller players rely on to protect their exposure including long-term supply arrangements, hedging and access to rail, it turns out that only about 20 per cent of oilsands supply is actually affected by the light-heavy differential. WTI is West Texas Intermediate light oil priced in Cushing, Oklahoma and WCS is Western Canadian Select heavy oil priced in Hardisty, Alberta. The WTI-WCS spread is referred to as the light-heavy differential. Alberta’s heavy oil is a low-quality crude that always sells at a discount to lighter, higher quality oil. It costs money to deliver it to Cushing which further reduces its price. The natural discount for quality and transportation is $15 US to $20 US per barrel which means if WTI is selling for $50 US a barrel we would expect WCS to sell for about $30 US to $35 US a barrel. However, even as WTI hovers around $50 US a barrel, the discount for WCS has fallen below the normal range for quality and transportation. The problem is, Notley claims the abnormal spread affects every barrel when relatively few barrels are actually exposed. Notley’s claim is based on an egregious error about how the market works. Oil producers have implemented price protection business strategies that ensure hardly any barrels are affected at all. Notley has frequently repeated this story since last spring when she started alarming the public claiming that the heavy oil discount was costing the Canadian economy $15 billion a year — $40 million a day. That estimate was lifted from a report prepared by Scotiabank which is replete with errors and it is a huge mistake to use that one report as the entire basis for any claim. Last week, Notley doubled the figure to $80 million a day and launched a Canada-wide ad campaign, including a Real Time Revenue Loss Calculator located near Parliament Hill. I asked the Alberta government how the $80 million a day was calculated and was advised that Notley once again relied on the flawed Scotiabank report. We’ve heard these false claims before It reminds me of a similar false narrative advanced in support of the Northern Gateway pipeline proposal, way back in 2012. A CIBC analyst claimed there was a $50 million a day loss because Northern Gateway was not built. When I asked for the calculation he did not have it. Natural Resources Minister, Joe Oliver aggressively relied on the figure in public statements. I asked Natural Resources Canada for their calculation and was given a run around. Eventually, an after-the-fact calculation was provided that made little sense. This didn’t stop the Canadian Chamber of Commerce from releasing a pamphlet in September 2013 claiming that same $50 million a day loss. That document was paid for by industry, including Kinder Morgan. I checked with the Chamber of Commerce. They did not confirm how the figure was derived but said they relied on sources like CIBC and Oliver. Flawed analysis makes Notley’s numbers meaningless Notley relies on the Scotiabank report which attempts to put some analysis behind its figure, but Scotiabank misrepresented how the market for crude oil actually works. Scotiabank mistakenly applied the discount to all barrels supplied as if they are all exposed to spot market pricing when relatively few are. What matters is not the size of the discount, but the number of barrels exposed to it. Reliance on a flawed Scotiabank analysis renders Notley’s claim meaningless. Take for example the integrated operations of major oil producers active in the Alberta economy. Scotiabank would have Canadians believe that when Suncor, Husky and Imperial sell the crude they produce to their refineries in Canada, they suffer a loss. They don’t. They make profits in their refinery operations — in Canada — as if they paid the international benchmark price, Brent, for their feedstock. Scotiabank would also have us believe that when other Canadian refiners — such as Regina Co-op, in Saskatchewan, or Parkland in B.C. — buy discounted crude, that this is a loss to the Canadian economy, when it is a clear gain. Since Scotiabank “forgot” that we have a refinery sector in Canada, this error alone overstated the number of barrels it subjected to its "loss" estimate by about 20 per cent. I asked Scotiabank about this. I was told that their report was not intended to be a cost benefit evaluation. When I said their report is presented as such, suddenly they had no further time for discussing the flaws in their analysis with me. There are a number of other major flaws in Scotiabank’s report. When crude oil producers deliver barrels to the U.S. Gulf Coast those barrels receive a higher price not determined by the WTI-WCS discount. Therefore, these barrels are not exposed to it. We know this because oil producers who deliver to the Gulf tell their investors they receive global pricing based on Mexican Maya heavy oil. This means that even more of the barrels Scotiabank subjected to the discount are actually not affected by it. Notley’s discount narrative presents big oil as if they have been caught totally unaware of market forces. Anyone who understands the buying and selling of Canada’s crude knows most barrels are protected from spot market pricing because major companies have spent years implementing business strategies to do so. Imperial Oil CEO, Rich Kruger, explained to investors in July how Imperial protects production: “We continue to reduce our overall exposure to differentials, through our own refineries, contract pipe to the Gulf Coast and continued expanded use of rail … As I look to the second half of the year, I expect that we will be using more of it (rail), notionally targeting something in the 125,000 barrels a day of the roughly 210,000 barrel a day capacity of the facility (Kearl). Here again, it is allowing us to cost effectively, through the use of unit trains and our existing ownership in this facility, compete on a netback basis with pipe alternatives to get to markets. Again, primarily Texas, Louisiana, Gulf Coast and get the highest realization for our production.” There are even more protection strategies from volatile spot market pricing. When crude oil producers enter into long-term contracts for space on pipelines such as Keystone and Express, they protect themselves with long term supply contracts with refiners. Producers will also enter into long-term supply contracts with refiners even when they rely on spot capacity for pipelines such as Enbridge mainline and Trans Mountain. The mid-west U.S. is the most significant market for western Canadian crude and many of the refineries rely on such arrangements with oil suppliers. When Canadian oil producers supply crude to their own refineries in the U.S., they also keep the benefit. Cenovus has invested in two refineries south of the border rather than investing in value added in Canada. This protects many of the barrels they produce from an abnormal discount. Integrated U.S. refinery protection, along with long-term contracts and access to rail is why Cenovus can report to its shareholders that its exposure to the wider differential is mitigated for 55–60 per cent of the heavy barrels that the company produces. How few barrels are actually exposed? It is difficult to get an accurate estimate of the number of barrels that are exposed to the light-heavy differential. Suncor, Husky and Imperial are effectively not exposed, while Cenovus and Canadian Natural Resources are partially exposed. These five companies represent close to 80 per cent of heavy oil exported. Evaluating oilsands players individually and incorporating the strategies even the smaller players rely on to protect their exposure including long-term supply arrangements, hedging and access to rail, suggests that in aggregate no more than 400,000 barrels a day — or about 20 per cent — of oilsands supply is affected by the light-heavy differential. The volume of supply exposed to the differential can vary depending on markets and other conditions. For example, when Keystone sprung a leak a year ago and was shut down, barrels under long term contract on that pipeline suddenly hit the spot market widening the differential significantly. The differential widened not because of a lack of pipeline capacity but because of a lack of pipeline integrity. Keystone capacity came back on stream pretty quickly and the differential narrowed. But then it began to widen once again. Pipelines were not full, but capacity was becoming constrained. Oil producers continued to increase production into a transportation-constrained market. Oil producers brought a deeper discount on themselves. For many of the big players, the net impact would be beneficial. Reality check on the need for new pipelines The second part of the misleading narrative around the deep discount says the abnormally wide differential is due to one factor — a lack of pipeline capacity. Therefore, the spread can only be narrowed to its normal range by building Trans Mountain’s expansion. The problem is, other factors are driving the steep discount and excess pipeline capacity will be available long before Trans Mountain is ever built. Earlier this year producers became more concerned about access to pipeline capacity. They began to nominate for pipeline space not only based on barrels they had available to ship, but for barrels they didn’t have. The industry has a term for these imaginary barrels — they call them “air barrels.” The idea is that, if they over-nominate for pipeline capacity and the pipeline operator apportions the space, they will get all the space they could possibly need. The problem is, exaggerating the barrels they have available comes at a cost to the system and the Canadian economy. Over-nomination leads to unused capacity. Pipeline space runs idle when oil producers abuse the system by nominating barrels they don’t have because Enbridge plans the batches as efficiently as possible at the beginning of the month, based on what the company was told. When those barrels don’t materialize, Enbridge is unable to replace them. Enbridge Executive vice president, Guy Jarvis, explains the air barrel problem this way: “We find ourselves, mid-month, falling short on crude … we've got to … make sure that those barrels that are nominated and granted space are real so that we can move them … what we're seeing is that the throughput at the end of the month versus what we accepted for nominations is not matching up.” Enbridge is reluctant to say how much space runs idle. Canadian Natural Resources estimated last spring that as much as 125,000 barrels a day of capacity on Enbridge Mainline is running empty because of air barrel nominations. Recent throughput statistics on Enbridge’s system suggest it could be closer to 150,000 barrels a day. Enbridge’s inefficient use of its pipeline capacity is significant. It produces a serious widening of the differential because it takes relatively few barrels in the spot market to do so. If Enbridge were able to run its pipeline at a higher rate of throughput, the discount would narrow to a more natural range based on quality and transportation costs. What’s stopping Enbridge from using its excess pipeline capacity? In June of this year Enbridge attempted to stop the inappropriate nominations for space on its system. This prompted BP to file a complaint with the National Energy Board which triggered a flurry of letters from industry players. A review of the correspondence makes it clear that when Enbridge attempted to verify nominations under a new regime it created winners and losers. The winners under the old system were not interested in changing the setup. If there were a genuine concern on the part of industry about a lack of capacity and harm from the discount, Enbridge’s flawed nomination process would have been corrected long ago. When this situation is more clearly understood, it makes Notley’s ad campaign and appointment of a special envoy to dig into the discount look cartoonish. At Justin Trudeau’s press conference at the Alberta Chamber of Commerce in Calgary last Thursday, the prime minister picked up the $80 million a day figure and stated that oil producers “are forced to sell our oil at a discount.” There is no forcing here. Nobody is making huge oil companies do anything. These companies are making Alberta and Ottawa do their bidding. Trudeau overpaid for an aging pipeline and the right to expand it so irresponsible producers can continue to exploit fossil fuels without constraint at a time when the world marketplace and global ecosystem is signaling it’s time to stop. There are few barrels affected by the deep discount, and for those barrels that are, the deep discount is being driven by a flawed nomination process and industry players that refuse to figure out a way to fix it. Even if Enbridge were able to stop the nomination of air barrels and efficiently use the capacity it has, expansion of oilsands production currently underway would see a return of constrained capacity. However, as the oil producers themselves tell us, this will be addressed by capacity expansions expected within the year. Enbridge’s Line 3 Replacement project will be complete in the fall of 2019 bringing 370,000 barrels a day of capacity on stream. With other enhancements the company has announced, a further 400,000 barrels a day can be made available. Expanded capacity of close to 800,000 barrels a day means — under the current outlook for crude oil production into the next decade — Trans Mountain’s capacity is not needed. Not only is Notley’s — and now Trudeau’s — $80 million a day deep discount narrative fundamentally flawed, the claim that only Trans Mountain’s expansion can solve it is also simply untrue.

Infection of Wildlife by Mycobacterium bovis in France Assessment Through a National Surveillance System

ORIGINAL RESEARCH ARTICLE Front. Vet. Sci., 30 October 2018 | https://doi.org/10.3389/fvets.2018.00262 , Sylvatub Édouard Réveillaud1†, Stéphanie Desvaux2*, Maria-Laura Boschiroli3, Jean Hars2, Éva Faure4, Alexandre Fediaevsky5†, Lisa Cavalerie5, Fabrice Chevalier5, Pierre Jabert5, Sylvie Poliak6, Isabelle Tourette7, Pascal Hendrikx1† and Céline Richomme8 1Anses, Unit of Coordination and Support to Surveillance, Maisons-Alfort, France 2French Hunting and Wildlife Agency (ONCFS), Studies and Research Department, Auffargis, France 3University Paris-Est–Anses, French Reference Laboratory for Tuberculosis, Maisons-Alfort, France 4National Hunters Federation (FNC), Issy-les-Moulineaux, France 5French General Directorate for Food (DGAL), Animal Health Unit, Paris, France 6French Association of Directors and Managers of Public Veterinary Laboratories of Analyses (Adilva), Paris, France 7French National Federation of Animal Health Defense Associations (GDS France), Paris, France 8Anses, Nancy Laboratory for Rabies and Wildlife, Malzéville, France Mycobacterium bovis infection was first described in free-ranging wildlife in France in 2001, with subsequent detection in hunter-harvested ungulates and badgers in areas where outbreaks of bovine tuberculosis (TB) were also detected in cattle. Increasing concerns regarding TB in wildlife led the French General Directorate for Food (DGAL) and the main institutions involved in animal health and wildlife management, to establish a national surveillance system for TB in free-ranging wildlife. This surveillance system is known as “Sylvatub.” The system coordinates the activities of various national and local partners. The main goal of Sylvatub is to detect and monitor M. bovis infection in wildlife through a combination of passive and active surveillance protocols adapted to the estimated risk level in each area of the country. Event-base surveillance relies on M. bovis identification (molecular detection) (i) in gross lesions detected in hunter-harvested ungulates, (ii) in ungulates that are found dead or dying, and (iii) in road-killed badgers. Additional targeted surveillance in badgers, wild boars and red deer is implemented on samples from trapped or hunted animals in at-risk areas. With the exception of one unexplained case in a wild boar, M. bovis infection in free-living wildlife has always been detected in the vicinity of cattle TB outbreaks with the same genotype of the infectious M. bovis strains. Since 2012, M. bovis was actively monitored in these infected areas and detected mainly in badgers and wild boars with apparent infection rates of 4.57–5.14% and 2.37–3.04%, respectively depending of the diagnostic test used (culture or PCR), the period and according to areas. Sporadic infection has also been detected in red deer and roe deer. This surveillance has demonstrated that M. bovis infection, in different areas of France, involves a multi-host system including cattle and wildlife. However, infection rates are lower than those observed in badgers in the United Kingdom or in wild boars in Spain. Introduction Wildlife can serve as a reservoir for multiple pathogens and may serve as a sentinel of the disease risk to humans and domestic animals. As a result, disease surveillance in wildlife is strongly recommended to provide data on the epidemiological role of wild animals and for the development of adapted disease control measures (1). Bovine tuberculosis (TB) is a contagious and zoonotic disease caused by Mycobacterium bovis, and occasionally by M. caprae or M. tuberculosis (hereafter referred to as MTBC). This pathogen primarily infects cattle but can be transmitted to a wide range of host mammals, especially numerous wild animals such as Eurasian badgers (Meles meles), wild boars (Sus scrofa), red deer (Cervus elaphus), and roe deer (Capreolus capreolus) (2). In the United Kingdom (UK) and in Ireland, the Eurasian badger is considered as TB reservoir, as is the wild boar in Spain. These species are involved in the transmission of M. bovis to cattle (3–6). France is officially declared TB-free since 2001 in the bovine population, because < 0.1% of cattle herds being infected annually. However, outbreaks still occur and the number of infected herds has increased since 2004 in certain parts of the country, especially in the South-West: Dordogne, Charente and Pyrénées-Atlantiques (French administrative division called departments) and in the East of France (Côte-d'Or) (7). In France, TB in wild animals was first detected in 2001 in the Brotonne forest (Normandy) in hunter-harvested red deer exhibiting gross lesions. In 2006, despite control measures (culling), apparent prevalence rates in this forest reached 24% in red deer and 42% in wild boars, the closed environment and high density of wild ungulates were considered major risk factors to explain such high prevalence rates (8). Elsewhere in France, sporadic cases of TB infection have been detected in red deer and/or wild boar in several areas: Côte-d'Or (Burgundy region), Corsica, Pyrénées-Atlantiques, Dordogne, and Ariège in 2002, 2003, 2005, and 2010, respectively. The first cases in wild ungulates were systematically detected by carcass examination in hunter-harvested animals. Since then, event-based surveillance programs (also called passive surveillance) and targeted (or active) surveillance programs for the disease including the badger have been implemented in these areas. TB infection in badgers was initially detected in 2009 in Côte-d'Or (5.7%, n = 918 in the 2009–2011 period), then in 2010 in Dordogne and Charente (4.8%, n = 417 in 2010–2011). In wild boars, prevalence rates observed in 2008 reached locally 16.5% in Côte-d'Or and 4.4% in 2010–2011 in Dordogne (9). All these cases were detected in the vicinity of cattle outbreaks (10–12). Increasing concern regarding the status of TB infections in wildlife led the French General Directorate for Food (DGAL) and the main institutions involved in animal health and wildlife management to establish a national surveillance system for TB in free-ranging wildlife: the “Sylvatub” system. This system coordinated by the French platform for epidemiological surveillance in animal health (ESA-Platform), was launched in September 2011. The main aims of Sylvatub are to detect TB in wildlife, to estimate and monitor infection levels in infected areas, to characterize M. bovis strains isolated from wildlife and to harmonize surveillance at the national level. This article summarizes the key data collected on TB infection in France between 2011 and 2017 in badgers, wild boars, red deer, and roe deer. We describe the organization of the Sylvatub system and the findings in terms of TB prevalence in wild boars and badgers, and necropsy data gathered during event-based and targeted surveillance in the four species. Materials and Methods Stakeholders and Organization of Sylvatub The organizational structure of the system is shown in Figure 1 and was described by Rivière et al. (12). Briefly, the DGAL is in charge of the Sylvatub system. Coordination and technical operations are performed by the ESA-Platform www.plateforme-esa.fr. National governance is ensured by a steering committee and a technical subcommittee, where the different institutions or organizations involved in Sylvatub are represented (Figure 1). FIGURE 1 www.frontiersin.org Figure 1. Simplified organization of Sylvatub. Steering committee members: French General Directorate for Food (DGAL), Ministry of the Environment (MEDDE), Regional Directorates for Food (DRAAF), Anses, French hunting and wildlife agency (ONCFS), National Hunters Federation (FNC), French association of pest control officers, French association of approved trappers, the French National Federation of Animal Health Defense Associations (GDS France), National veterinary association (SNGTV), Coop de France and French Association of Directors and Managers of Public Veterinary Laboratories of Analyzes (Adilva), Regional veterinary epidemiologists. Technical subcommittee members: DGAL, Anses, ONCFS, DRAAF, FNC, GDS France, Adilva. The implementation of Sylvatub is based on the regular involvement of national stakeholders [national reference laboratory (NRL) for TB and the national coordinator of Sylvatub] and local stakeholders: veterinary services in charge of Sylvatub coordination, public administration in charge of the environment, hunting federations, associations of “lieutenants de louveterie” (historically called wolf-hunter, nowadays being state but volunteer officers in charge of pest control and who supervised badger trapping), trappers associations (volunteers who are duly trained and authorized), French hunting and wildlife agency services, local veterinary laboratories for animal health, cattle breeders, and finally veterinary associations. Sylvatub: A Risk-Based Surveillance System Sylvatub targets the wildlife species considered in 2011 to be the most relevant in the TB multi-host system: badgers, wild boars, red deer, and roe deer. Sylvatub's surveillance system components are based on event-based and targeted surveillance. These components are applied according to a risk-based surveillance approach, with three different levels of surveillance, applied at the level of French department (Table 1) and defined as follows: - Level 3, for areas with several outbreaks in cattle and cases in wildlife. This level is applied for at least 4 years, to monitor infection levels in wildlife and to assess the efficacy of control measures; - Level 2, for areas with sporadic at-risk outbreaks in cattle and/or areas in geographic proximity to high-risk areas. This level is applied for at least 1 year or for as long as necessary to develop a clear understanding of the epidemiological situation. A lower or higher surveillance level is subsequently applied, depending on the results obtained; - Level 1, elsewhere in the country where no domestic and wild animal has been found infected for a long period of time. TABLE 1 www.frontiersin.org Table 1. Surveillance methods implemented depending on the estimated risk level. The local surveillance level is re-evaluated twice a year, to align with the epidemiological situation in cattle and wildlife populations. Event-Based Surveillance Through Detailed Game Carcass Examination This surveillance component is applied to all geographic areas, i.e., regardless of the local risk, to hunted wild boars, red deer, and roe deer. It is based on the analysis of animals with macroscopic TB-like lesions detected by hunters during post-mortem examination of all hunted games. The detection of gross lesions is supported by a national network of more than 55,000 hunters trained by the National Hunters Federation (FNC) for food safety purpose. Additionally to this framework, voluntary training courses were organized in the field to train hunters for recognition and reporting of TB-like lesions (internal abscesses or gross lymph nodes) and sampling of affected organs. Event-Based Surveillance Through the SAGIR Network: Wild Animals Found Dead, Moribund or With Abnormal Behavior Event-based surveillance on dead and dying wild animals, through the SAGIR network (French hunting and wildlife agency/local hunters federations/FNC), has been implemented in France since 1986 (13). Within the Sylvatub system, dead animals belonging to TB-receptive species (badgers, wild boars, red, and roe deer) collected as part of the SAGIR network are tested for TB (i) in the presence of TB-like lesions for level 1 departments, and (ii) systematically for level 2 and 3 departments. Moreover, efforts are made to collect and test road-kill badgers in all the level 2 and 3 departments. Targeted Surveillance Targeted surveillance may concern badgers, wild boars and/or red deer in level 3 departments depending on the population abundance and distribution, and badgers only in level 2 departments. This component of surveillance is implemented in “at-risk areas” determined as areas of about seven kilometers in radius around pastures of cattle outbreaks detected in the previous 4 years, and hunting or trapping locations of all infected wild animals. For badgers, at-risk areas are divided in two sub-areas: “infected area” (2 km radius) and “buffer area” (5 km radius around the infected area) to take into consideration badger home range which is smaller than in wild ungulates. Sample sizes are determined to detect TB infection in at-risk areas, assuming a prevalence of 3%, with a 95% confidence interval. For wild boar and red deer, samples are defined for the whole at-risk area, whereas for badgers, one sample is for the infected area and one is for the buffer area. In large areas where wild populations could be considered as infinite, a sample of 130 animals per species is required. This sample size takes into account diagnostic test sensitivity (estimated at ~75% for PCR; see below). However, sample sizes are adjusted based on the surface of the area. In practice, samples between 60 and 260 red deer, wild boars, and badgers are programmed annually in each area. These are samples of hunted wild boars and deer or trapped badgers for control measures in infected areas. Additionally, around sporadic cattle outbreaks outside at-risk areas (in level 2 and 3 departments), systematic TB analysis is conducted on a sample of about 15 badgers trapped within a radius of one or two kilometers depending on the number and localization of badger's setts. These small areas are called “prospecting areas.” Animals are collected even if no macroscopic TB lesions are detected by field stakeholders. Tissue Collection and Laboratory Investigations Sample Collection Wild boars and red deer are collected by hunters, under the supervision of the local hunting federations during the hunting season (generally from August to March each year), and badgers are collected by trappers (accreditation required), under the supervision of pest control officers. In infected areas, where one of the control measures is to reduce badger populations, badger can be trapped, mostly from March to August. Field stakeholders (hunters, trappers, pest control officers) submit animals, organs, or tissues (from a standardized list of samples described in Tables 2, 3) directly to the local laboratory or store them in cooling rooms or freezers for later analysis. Data is collected for each animal on the species, estimated age (juvenile or adult), sex, date, location of collection and body condition (degradation, presence of lesions in the carcass, etc.). Age determination is based on animal size for badgers and/or weight and hunters' knowledge for wild ungulates. Trappers and pest control officers are volunteers but a financial compensation is provided for them. TABLE 2 www.frontiersin.org Table 2. Diagnostic methods used in badgers from 2012 to 2017. TABLE 3 www.frontiersin.org Table 3. Diagnostic methods used in wild boars and deer for the hunting seasons from 2011 to 2017. Tissue samples are taken in local laboratories even if no TB-like lesions are detected except for SAGIR network animals in level 1 department. Tables 2, 3 shows the field samples collected for testing and changes over time. For wild boars, from mid-2013 until the present time, only the head has been collected and the submaxillary lymph nodes are tested. For badgers, which are relatively small, the entire animal is collected. Analyses at the local laboratory consist of post-mortem necropsy to detect TB-like lesions (caseo-granulomas, mineralized nodules, or purulent abscesses), polymerase chain reaction (PCR) and/or bacterial culture on pooled lymph node samples and on pooled samples with TB-like lesions. As presented previously, diagnostic schemes differ between surveillance components: either TB testing is performed only if TB lesions are detected (SAGIR event-based surveillance in level 1 departments), or TB testing is performed systematically (for all suspect hunted carcasses and all SAGIR animals in level 2 and 3 departments, as well as for targeted surveillance in level 2 and 3 departments). Analyses are performed as indicated in Tables 2, 3. The year 2015 marked a diagnostic-methodological transition for badger surveillance as these two diagnostic schemes were used depending on the local laboratory and the time of year. Changing from culture to PCR as a first line test was decided after having demonstrated that in cattle PCR provides a better sensitivity for TB detection without losing specificity (14). Microbiological Culture Bacterial culture is performed following the protocol established by the French NRL (NF U 47–104) for isolation of M. bovis. Two to 5 g of sampled tissues were crushed with a 4% sulfuric acid solution to decontaminate the tissue. After 10 min, the acid was neutralized by adding a 6% sodium hydroxide solution. After decontamination, the supernatant was seeded on two different media: Löwenstein-Jensen and Coletsos. All seeded media were incubated at 37°C +/– 3°C for three months and exanimated every 2 weeks. If contamination is observed during the first month, samples are decontaminated a second time with 4% sodium hydroxide and then neutralized with 10% sulfuric acid solution. The isolated M. tuberculosis complex (MTBC) colonies are confirmed by DNA amplification (15) targeting the IS6110 sequence present in all species of MTBC (16), and M. bovis is confirmed by spoligotyping (see below). Tissue PCRs DNA extraction is performed on a pool of lymph nodes (retropharyngeal, pulmonary and mesenteric) and on organs with gross lesions when present, after mechanical lysis using an LSI MagVet™ Universal Isolation Kit (Life Technologies) with a KingFisher™ Flex automate (Thermo Scientific), following the manufacturer's instructions. The LSIV and MAX™ MTBC Real-Time PCR kit (Life Technologies), which targets IS6110, is used. A volume of 5 μL of the extracted DNA is mixed with 20 μL of reaction mix, and the reaction is carried out at 50°C for two min (1 cycle), followed by one cycle of 10 min at 95°C and 45 cycles of 15 s at 95°C, and one min at 60°C. Results are interpreted following the manufacturer's recommendations and by comParison with negative and positive controls. If DNA amplification is positive, M. bovis or any other MTBC species is confirmed by spoligotyping (see below). Spoligotyping Spoligotyping is performed as described by Zhang et al. (17), using TB-SPOL kits purchased from Beamedex® (Beamedex SAS, Orsay, France) on Bio-PLex 200/Luminex 200®. Molecular typing is performed either on MTBC isolates or directly on PCR-positive sample DNA. The presence or absence of the 43 spacer sequences contained in the DR locus is represented in a binary code of 43 entries. Spoligotypes are named according to an agreed international convention (www.mbovis.org). Data Analysis An infected animal is defined as an animal with an analytical result demonstrating M. bovis (or if it had been found M. tuberculosis or M. caprae) by molecular diagnosis or by bacterial culture. All results presented in this article come from the Sylvatub national database. Results are presented by calendar year for badgers and by 12 month period starting with the beginning of the wild boar hunt (August to the end of July). The Sylvatub system was set up in September 2011; as a result surveillance findings for wild ungulates are presented from the 2011–2012 hunting season to the 2016–2017 hunting season and from 2012 to 2017 for badgers. To simplify, at-risk areas are renamed with numbers as follows, by chronological order of detection of TB in wildlife: 1: Brotonne-Mauny forest (Seine-Maritime); 2: Côte-d'Or; 3: Dordogne/Charente/Charente-Maritime/Haute-Vienne/Corrèze/Gironde; 4: Dordogne/Lot; 5: Béarn (Pyrénées-Atlantiques/Landes/Gers); 6: Ardennes/Marne; 7: Marne (Reims mountain); 8: Loir-et-Cher (Sologne); 9: Lot-et-Garonne; 10: Pays Basque; and 11: Ariège/Haute-Garonne (Figure 2). FIGURE 2 www.frontiersin.org Figure 2. Changes in surveillance levels and at-risk areas between 2012 (A) and 2017 (B) (1: Brotonne-Mauny forest; 2: Côte-d'Or; 3: Dordogne/Charente/Charente-Maritime/Haute-Vienne/Corrèze/Gironde; 4: Dordogne/Lot; 5: Béarn; 6: Ardennes/Marne; 7: Marne (Reims Mountain); 8: Loir-et-Cher (Sologne); 9: Lot-et-Garonne; 10: Pays Basque; 11: Ariège/Haute-Garonne). In this paper, apparent prevalence rates are indicated based on the diagnostic test used (culture or PCR). Furthermore, results were aggregated into two periods of 2 years each to calculate prevalence rates with more precision: P1 (2013 and 2014 for badger surveillance; the 2012-2013 and 2013-2014 hunting seasons for wild ungulate surveillance) and P2 (2016 and 2017 for badger surveillance; the 2015-2016 and 2016-2017 hunting seasons for wild ungulate surveillance). In P1, the diagnostic test used was sample culture, whereas in P2, PCR was used. We focused on areas where sampled animals were most numerous and where infection was confirmed to present and compare these results. To compare results in badgers between event-based and targeted surveillances, we focused in the at-risk area 3 because it is the only area where the number of analyzed badgers was sufficient for each of these surveillance components. Regarding the number of analyzed animals, we counted only those with an interpretable analysis result (positive or negative). Apparent prevalence and 95% confidence intervals were calculated using exact binomial tests and p-values using the Fisher's exact test. Data analysis was performed using LibreOffice Calc (version 5.2) and R Studio software (version 3.3.1). Maps were generated using QGIS software (version 2.16.3). Results Functioning Results Since its implementation in 2012, Sylvatub has been gradually strengthened due to the larger number of areas where wild animals have been found infected, the enlargement of infected areas affecting cattle, and the detection of sporadic cattle outbreaks in new areas. This is reflected in the increase of number of departments at level 2 and 3 (from 21 in 2012 to 32 in 2017) (Figure 2). The surveillance levels for the departments were re-evaluated by the steering committee 10 times between 2011 and the end of 2017. In 2012, there were five distinct at-risk areas. Since then, six other at-risk areas have been defined, with a total of 11 areas in 2017. Targeted surveillance was implemented for wild boars and red deer in three at-risk areas (numbered 1, 7, and 8), for wild boars and badgers in four at-risk areas (numbered 9, 5, 10, and 11) and for the three species in four at-risk areas (numbered 2, 3, 4, and 6) depending on the populations abundance and distribution. In the meantime, size of these at-risk areas was expanded for five areas (3, 4, 6, 10, and 11), reduced for two areas (2 and 5) and remained approximately stable for the others (see details in Supplementary Table 1). The surface area of mainland France classified as at-risk was 14,397 km2 in 2012 and 20,434 km2 in 2017. Event-Based Surveillance The number of wild boars, red and roe deer collected by event-based surveillance increased from 77 in 2011–2012 to 134 in 2015–2016. In total, 316 wild boars, 197 roe deer, and 98 red deer have been collected since 2011. The number of dead or dying badgers collected per year (SAGIR and road-killed badgers) has increased from 70 badgers in 2012 to 582 in 2015. This number has been stable since 2015 with about 580 badgers collected per year, most of them being road-killed badgers. Targeted Surveillance An average of 296 red deer (min: 226; max: 380), 1,420 wild boars (min: 1,078; max: 2,175) and 1,881 badgers (min: 1,447; max: 2,239) were analyzed per year between 2011 and 2017. TB Infection in Wildlife TB Infection in Badgers Event-based surveillance Among the 2,491 badgers collected by event-based surveillance in 45 departments, 2,397 were analyzed (2,372 with an interpretable analysis result), and 89 were found infected with M. bovis (Figure 3). In all, 84 of these infected animals were found in the vicinity of cattle outbreaks (75 infected badgers in infected areas, five in buffer areas and four in prospecting areas). Five infected badgers (n = 716) were from outside but very close (<3.5 km) to at-risk areas (areas 3 and 9). In infected area 3, where badgers collected by event-based surveillance are numerous, apparent prevalence rates seems to be stable between P1 (8.2%; 95% CI: 4.2–14.2%) and P2 (9.6%; 95% CI: 6.8–13.1%). FIGURE 3 www.frontiersin.org Figure 3. Location of badgers collected and found infected by event-based surveillance from 2012 to 2017. Targeted surveillance From 2012 to 2017, 378 badgers (n = 10,184) were found infected with M. bovis by targeted surveillance in at-risk areas 2, 3, 4, 5, 6, 9, 10, and 11. In all, 340 of these badgers (n = 6,870) originated from infected areas and 27 (n = 3,314) from buffer areas (Figure 4). Targeted surveillance has not been implemented in at-risk areas 1, 7 and 8, where badger populations are very small. FIGURE 4 www.frontiersin.org Figure 4. Location of infected badgers collected by targeted surveillance from 2012 to 2017 (2: Côte-d'Or; 3: Dordogne/Charente/Charente-Maritime/Haute-Vienne/Corrèze/Gironde; 4: Dordogne/Lot; 5: Béarn; 6: Ardennes/Marne; 9: Lot-et-Garonne; 10: Pays Basque; 11: Ariège/Haute-Garonne). In infected areas, apparent prevalence rate observed with culture (from 2012 to 2014) was on average 4.57% (n = 3,198) and with PCR (2016-2017) on average 5.14% (n = 2,412) (Supplementary Table 2). In buffer areas, apparent prevalence rate observed with culture was on average 1.33% (n = 1,508) and with PCR on average 0.41% (n = 1,217) (Supplementary Table 2). Regarding results in the four main infected areas (areas 2, 3, 5 and 6) for the two periods (P1 and P2), prevalence in badgers was significantly lower in P1 in infected area 3 than in the three other areas (p < 0.001; p = 0.009; p = 0.0351, respectively). In P2, prevalence was higher in infected area 5 than in areas 2 and 3 (p = 0.02; p = 0.013, respectively) (Table 4). TABLE 4 www.frontiersin.org Table 4. Apparent prevalence rates in badgers collected by targeted surveillance in the four main infected areas of France between 2013-2014 (Period 1: P1) and 2016-2017 (Period 2: P2) [percentages are given with 95% confidence intervals (CI); in brackets number of infected/analyzed animals]. In area 2, apparent prevalence was higher in P1 than in P2 (p = 0.008) (Table 4). The targeted surveillance in prospecting areas has detected two sites of infection: in Ardennes in 2013, five infected badgers were detected from a total sample of 37 badgers collected close to four bovine TB outbreaks and, in 2015, in the Pays Basque (Pyrénées-Atlantiques), two infected badgers were detected from a sample of nine badgers, also sampled on the outskirts of four bovine TB outbreaks. As a result of these findings, infected and buffer areas were defined in these two departments and other cattle outbreaks were discovered nearby. Males were found to have significantly higher infection rates (4.95%, n = 3,394) than females (2.02%, n = 4,213) (p < 0.001). In infected area 3, prevalence were significantly higher (in P1 and P2) in badgers collected by event-based surveillance (mainly road-killed badgers) than by targeted surveillance (mainly trapped badgers) (p = 0.006 and p = 0.01, respectively) (Table 5). TABLE 5 www.frontiersin.org Table 5. Comparison of apparent prevalence rates in badgers obtained by event-based surveillance and by targeted surveillance for two periods in infected area 3 [percentages are given with 95% confidence intervals (CI); in brackets number of infected/analyzed animals]. TB Infection in Wild Boars and Deer Event-based surveillance Among the 323 free ranging wild boars collected from 2011–2012 to 2016–2017 in 53 departments, 258 were analyzed, 241 had an interpretable analysis result and 29 were found to be infected in six departments (Dordogne, Charente, Côte-d'Or, Haute-Corse, Corse-du-Sud, and Loir-et-Cher). Ten came from at-risk areas (level 2 and 3 departments), 18 came from Corsica and one wild boar found infected in January 2015 in Loir-et-Cher, a livestock TB-free area since 1986 (Figure 5). This wild boar was found in open forest, although the area is surrounded by private game parks. M. bovis was also isolated from a wild boar in a closed game park in the Reims Mountain (Marne) in 2012 (18). Data for this case were not integrated in Sylvatub database because it was not a free ranging wildlife animal. FIGURE 5 www.frontiersin.org Figure 5. Location of wild ungulates collected by event-based surveillance from 2011 to 2017. A total of 107 red deer and 190 roe deer have been collected through event-based surveillance since 2011 from 35 and 48 departments, respectively. Two red deer submitted by hunters both in 2016 were found to be infected in areas 2 and 3, and five infected roe deer were detected in area 3 in 2012, 2013, 2015, and 2016. For more details on roe deer surveillance in France see Lambert et al. (19) (Figure 5). Targeted surveillance Targeted surveillance on wild boars was implemented in 11 at-risk areas with 7,634 wild boars analyzed since 2011. In total, 180 wild boars were found infected with M. bovis in seven at-risk areas. In at-risk areas where infection in wild boars was known, apparent prevalence rate observed with culture (from 2011 to 2015) was on average 3.04% (n = 3,786), and with PCR (2015–2017) on average 2.37% (n = 2,536) (Supplementary Table 3). Prevalence in the main at-risk areas was between 1.5 and 4.3% in P1, and between 0.5 and 4.4% in P2 (Table 6). No infected wild boar has been found in areas 6, 7, 8, and 10 (Supplementary Table 3). In the Brotonne-Mauny forest (area 1) surveillance in wild boars has been implemented since 2001 due to the detection of infection at high prevalence rates in deer and wild boars (20). From that time point onwards, one to five additional infected wild boars were found each year between 2011 and 2017 (among about 200 wild boars analyzed/year) (Supplementary Table 3). Furthermore, following the discovery of one infected wild boar in Loir-et-Cher (Sologne), 986 wild boars were analyzed from 2015 to 2017 in open forest and in 12 game parks, but no additional wild boar was found to be infected. TABLE 6 www.frontiersin.org Table 6. Apparent prevalence rates in wild boars in at-risk areas of France where infection has been found in wild boars in the 2012-2013-2014 period and the 2015-2016-2017 period [percentages are given with 95% confidence intervals (CI); in brackets number of infected/analyzed animals]. Infection in males and in females was similar (2.4%, n = 2,947 and 2.5%, n = 2,753, respectively) (p = 0.80). Targeted surveillance on red deer was implemented in seven at-risk areas, where 1,817 red deer carcasses have been examined including 1,491 analyzed since 2011. Six red deer were found infected in area 2. Results by year and by area are detailed in Supplementary Table 4. M. bovis Strains Isolated in Wildlife In total, nine genotypes of M. bovis have been identified in wildlife in France (Figure 6). Some of these genotypes are found in different at-risk areas (SB0120 in areas 2, 3, and 6 and in the Corsica region, SB134 in areas 1, 2, and 11), but their variable number tandem repeat (VNTR) profiles are different (Table 7). We should note the presence of two different genotypes in two areas: SB0120 and SB0134 in area 2, and SB0120 and SB0840 in Corsica. In area 5, the two genotypes SB0821 and SB0832 are in geographic proximity, but nevertheless in different sectors. FIGURE 6 www.frontiersin.org Figure 6. Location of M. bovis strains in wildlife in France (1: Brotonne-Mauny forest; 2: Côte-d'Or; 3: Dordogne/Charente/Charente-Maritime/Haute-Vienne/Corrèze/Gironde; 4: Dordogne/Lot; 5: Béarn; 6: Ardennes/Marne; 7: Marne (Reims Mountain); 8: Loir-et-Cher (Sologne); 9: Lot-et-Garonne; 10: Pays Basque; 11: Ariège/Haute-Garonne). TABLE 7 www.frontiersin.org Table 7. Genotype of M. bovis strains in wildlife in France. Gross Lesions and TB Infection Lesions in Badgers Among 357 badgers out of 13,620 (2.6%) necropsied showed TB-like lesions. Of these, 95 were found to be infected. Furthermore, only 21.5% of the 442 infected badgers showed TB-like lesions. Lesions were mostly found in the cephalic lymph nodes (retropharyngeal and submandibular) and the pulmonary tractus (lung, bronchial and mediastinal lymph nodes). In total, eight infected badgers had TB-like lesions on at least two internal organs and at least two lymph nodes. 16.2% of infected badgers (47/291) collected by targeted surveillance showed TB-like lesions, whereas in infected badgers collected by event-based surveillance, 31.0% (22/71) showed TB-like lesions (p = 0.04). Lesions in Wild Boars In all, 526 wild boars out of 7,838 (6.7%) collected by targeted surveillance showed TB-like lesions, and 77.8% of the infected wild boars showed TB-like lesions. Most of the TB-like lesions were found in the submandibular lymph nodes. Lesions in Deer Among the eight red deer found infected since 2011, six came from targeted surveillance and two from event-based surveillance (submitted by hunters because of visible TB-like lesions). Five red deer showed gross TB-like lesions: in the pulmonary system for three red deer, in retropharyngeal lymph nodes for three, in mesenteric lymph nodes for one and in the liver for one. Gross TB lesions were also observed in infected roe deer (19). Discussion Organization of the Surveillance System Surveillance of TB in wildlife on a national scale in France, coordinated by the Sylvatub system, has been implemented gradually since 2011 thanks to the strong contribution of stakeholders at the national or local levels. Thanks to the involvement of hunters, event-based surveillance through detailed game carcass examination has often enabled us to detect first cases of TB in wild ungulates before targeted surveillance is deployed. It has help to detect TB as early as possible. However, the main challenge for Sylvatub lies in the involvement of volunteer actors (hunters, trappers, pest control officers) and local veterinary services in such a complex multi-partner network. The targeted surveillance recommended in the Level 2 and 3 departments required a particularly strong involvement of local volunteers to collect tissue samples of wild ungulates and to trap badgers, explaining why some targeted plans have only been partially implemented in some areas. And these volunteers are, for the large majority, not those who are directly impacted by TB in cattle (cattle breeders) but could be affected by negative consequences if infection is found in wildlife, as for example, the implementation of density control measures of wild ungulates. Furthermore, in some departments, surveillance has been renewed for many years, which leads to a weariness of local actors. It should also be noted that the cost of Sylvatub is important for the government since it amounts to about 1 million euros per year. Sampling and Diagnostic Protocols For each surveillance component, sampling was opportunistic and not performed randomly: for targeted surveillance it was based on trapper and hunter activity, and for event-based surveillance on different field actor interventions. Some areas or sectors were overrepresented whereas others were underrepresented depending on the number of volunteers, the intensity of their activity and the possibility to hunt. Moreover, samples collected were not strictly homogeneous from 1 year to the next, even within the same area. For event-based surveillance, the collection of carcasses or the reporting of animals with TB-like lesions strongly depend on the awareness of actors in the field. We can reasonably expect that this awareness is generally greater for in the departments affected by TB (level 2 and 3 departments) which constitutes a selection bias. In addition, wildlife surveillance must deal with unknown parameters such as densities, distribution, or the social behavior of animals. Surveillance must therefore adapt as well as possible to this variability and propose reasonable, realistic and attainable objectives but prevalence estimates are certainly biased. For example, it is difficult to set badger surveillance objectives without full knowledge of their densities and distribution. In practice, the samples planned in at-risk areas therefore had to be adjusted to the size of the area. We have set the design prevalence for sample size calculations at 3%. This threshold was chosen to be able to detect a relatively low prevalence while minimizing the sample size and therefore the cost. It could have affected the ability to detect TB in areas where TB is only present at prevalence below 3%, particularly in deer where prevalence seems lower than in the others species. The amount of time dedicated to post-mortem examinations and their thoroughness influence the detection of visible lesions (5, 21). Here, wild ungulates were not always examined in a standardized way by hunters in the field. Even though training is provided, detection of lesions suggestive of TB by hunters in the field is less sensitive than the necropsy performed in the laboratory. Nevertheless, in some laboratories, necropsy of badgers or ungulates is sometimes performed without thoroughly inspecting all lymphatic nodes and organs. In addition, for wild ungulates, only organ blocks (head, lungs and mesenteric apparatus depending on the species and year) are transmitted to the local laboratories as part of targeted surveillance. For all these reasons, the frequency of lesions has certainly been underestimated. Since 2011, the protocol for sampling biological tissue and the composition of analyzed pools of tissues have changed. Before 2014, for badgers, salivary glands were sampled and mixed with lymphatic nodes. For wild boars, since 2014, only the cephalic lymph nodes have been sampled and analyzed whereas before the pulmonary lymph nodes were also analyzed. The purpose of these changes was to concentrate the tissue pools with the organs most likely to be contaminated by M. bovis, in order to increase diagnostic sensitivity. Unfortunately, the impact of these measures could not be assessed (22, 23). Moreover, the type of analysis used for TB diagnosis changed from 2015: bacterial culture was used from 2011 to 2014 and then, from 2015, PCR was deployed. The year 2015 was a year of transition with the use of culture or PCR, depending on the local laboratory. Sensitivities were estimated in cattle populations by Courcoul et al. (14): on average 87.7% [82.5–92.3%] for PCR vs. 78.1% [72.9–82.8%] for culture. Culture sensitivity is probably lower when used for wild animals due to field conditions and the potential contamination and degradation of samples and because only a limited range of tissues are collected and analyzed from each wild animal. Furthermore, pooled samples are analyzed for wildlife, whereas cattle samples are analyzed separately. All together these factors lead to a decreased culture sensitivity estimated by about 30–40% and PCR sensitivity by about 10–20% (Boschiroli, personal communication) compared to those in cattle. In order to calculate prevalence more accurately, we grouped the results into two periods: P1 (2012–2014—use of culture) and P2 (2016–2017—use of PCR), and we calculated apparent prevalence. These prevalence rates do not take into account the sensitivity of the two analytical methods. For comparison of results in badgers, the year 2012 was not taken into consideration because it was the first year of operation of the Sylvatub system with a protocol that was not always fully implemented. The year 2015 was also ruled out because of the use of both analytical methods, depending on the local laboratory. M. bovis Infection in Wildlife Distribution of Infected Wild Animals All infected wild animals detected since 2012 have been found in the vicinity of cattle outbreaks (in at-risk areas up to 10 km from recent cattle outbreaks pastures), except for one wild boar found in Loir-et-Cher (Sologne), an area without known TB infection. The molecular profile of the M. bovis strain (SB0140; VNTR profile: 7 5 6 3 10 3 4 7) found in this wild boar was identical to that of a bovine animal slaughtered in Vendée (western France) in 1997. This profile is currently unknown outside of France, which appears to indicate that the infection originated within the country. However, cattle monitoring revealed no cases in herds located or grazing within 5 km of where the infected wild boar was found (844 cattle tested using the comparative intradermal tuberculin test, all negative) (24). Moreover, targeted surveillance in wild boar and red deer populations from open and closed areas (game parks) in a perimeter of 12 km around the index case has been implemented since the 2015–2016 hunting season without any infected animal having being discovered. There is no clear evidence about the origin of this case to date but it seems essential that the greatest vigilance be given to game parks and associated game movements. Infected wild boars were found in all at-risk areas except in the area of Ardennes-Marne (area 6) which is the only area where no infected wild boars were found despite 4 years of targeted surveillance. Infected badgers were mainly found in infected areas. A few were found in buffer areas (2–7 km from recent cattle outbreaks pastures) and only five from TB-free areas surrounding buffer areas. These five infected badgers were collected by event-based surveillance very close to at-risk areas (<3.5 km), and four of these five badgers were collected in 2012 and 2013 when perimeters of at-risk areas were not well defined. The discovery of these badgers has led to strengthened surveillance in cattle and subsequent detection of bovine outbreaks. However, the absence of TB detection in TB-free areas should be interpreted with caution due to the limited sampling size. In the UK, infected badgers were also detected between 1972 and 1993 in TB-free areas. In Ireland, this prevalence was estimated to be 15% in places where TB had not been reported in cattle for 6 years (25). All isolates obtained from infected wild animals exhibited the same genotypes that had already been found in isolates from cattle outbreaks in the same regions. In areas where two different genotypes are isolated in wildlife, we observe exactly the same two genotypes in cattle. Strains with the SB0120 or the SB0134 spoligotypes are present in cattle and wildlife in different regions in France albeit presenting different VNTR profiles (26, 27). These results highlight the epidemiological relationship between wildlife and cattle, and evidence that M. bovis infection spreads within a multi-species system in these areas as also observed in the UK, Ireland and Spain (28–31). The current risk is that complex reservoirs of M. bovis including one or more wild populations and the environment are locally constituted. Badger and wild boar are at the moment the two species most found infected (see sanitary results) and thus worrying in terms of maintenance community. But recent finding on red foxes in France (32) and in other regions of continental Europe (33) raises questions about the epidemiological role of foxes, and have motivated ongoing investigations in different endemic areas. Location of Lesions The location of lesions in badgers observed in France is consistent with previous studies carried out in the UK and in Ireland: the thoracic cavity (lungs and lymph nodes) and cephalic lymph nodes were the most common sites (3–5, 34, 35). As in these two countries, the presence of visible lesions only on lymph nodes was the most frequent finding. With regard to wild boars, lesions are generally smaller and confined to the lymphatic nodes of the head (mainly submandibular lymph nodes) and are therefore less visible to hunters at the time of carcass examination. Systematic inspection of these lymph nodes in the laboratory or by a trained person is therefore essential. The fact that the majority of infected deer have TB-like lesions and that these lesions are generally located in the pulmonary system makes it possible to suggest that surveillance by careful hunter examination and reporting observed lesions, remains a relevant and sensitive surveillance modality. Prevalence of M. bovis Infection Concerning deer, we have observed only a few M. bovis-positive cases since 2012 (eight red deer and five roe deer) in France, all of them from Côte-d'Or and Dordogne/Charente (areas 2 and 3) which are infected areas with large deer populations, the presence of numerous cattle-TB outbreaks, confirmed infection in badgers and wild boars. These observations suggest a more minor role of deer in the interspecific transmission of M. bovis in France compared to other species such as wild boars or badgers. These results are similar to those obtained in others European countries, especially in the Czech Republic, in Hungary where sporadic cases were observed in red deer or in Poland and Italy in roe deer (36, 37). In Austria, red deer infected with M. caprae have been found since 1999 (38). In the UK, a large-scale study was conducted in 2007 and revealed a prevalence of 1.02% in red deer (n = 196) and 1.02% in roe deer (n = 885) (39). The epidemiological situation of the Brotonne-Mauny forest (area 1) is special for France because of the very high prevalence level in red deer which were considered a TB maintenance host in the early 2000s (8, 9). This situation was also observed in southern Spain (P = 27.4%, n = 95 in the Doñana National Park) (40) and in Portugal between 2009 and 2013 (P = 38.3%, n = 115) (33). The wild boar is considered a key maintenance host for tuberculosis in Spain with prevalence >50% in areas with high-density populations, such as in the Doñana National Park or in large hunting parks (22, 41). In Portugal, prevalence rates ranging from 6 to 46% have been observed (bacterial culture on a pool of lymph nodes) (42). Infected wild boars are commonly discovered in Germany, Italy and in several countries of Central Europe (43, 44). In France, prevalence in wild boars is mostly lower [on average 3.04% in the 2011–2015 period (with culture) and 2.37% in the 2016–2017 period (with PCR)] than that observed in badgers in the same areas. This epidemiological situation is very different from that observed in south and central Spain where the wild boar is considered a key maintenance host for tuberculosis with prevalence >50% in areas with high-density populations, such as in the Doñana National Park or in large hunting parks (22, 41). In Portugal, prevalence rates ranging from 6 to 46% have been observed (bacterial culture on a pool of lymph nodes) (42). Infected wild boars are also commonly discovered in Germany, Italy and in several countries of Central Europe (43, 44). Finally, outside the Sylvatub system, TB was also detected in 2012 in 7.3% of a wild boar population from a game park in the Marne, a cattle TB-free area (18). This detection raised questions on disease surveillance in captive wild animals, especially in game parks. The prevalence observed in badgers in French infected areas was lower than that found in the bovine infection areas in the UK and Ireland. The prevalence rates estimated by culture in the UK during the randomized badgers culling trial, carried out between 1998 and 2006, varied widely (1.6–37.2%) depending on the post-mortem and culture methods used, with an average of 16.6% (3). In Ireland, 19.5 to 26.1% of the badgers analyzed by culture in the four study areas were found to be positive (45). A more recent study, in areas where there is high prevalence of bovine TB based on detailed post-mortem examination, histopathology, and culture in each specimen, reported a prevalence of 36.3% (4). Analysis of prevalence rates in ~5,000 badgers in Ireland revealed a decrease in the overall prevalence from 26 to 11% between 2007 and 2011 (46). In parallel, it should be noted that the herd prevalence in cattle in the UK and in Ireland is higher than in France (5–6 vs. 0.04%), and that all the analyzed badgers in these countries originated from areas with the highest prevalence in cattle (47). In the north of Spain, in the provinces of Galicia and Asturias, where TB prevalence in cattle is between 0 and 4.3% depending on the district, badger prevalence rates between 6 and 7% are observed (28), which is similar to rates observed in some areas of France. It is not possible to draw any conclusion on the relationship between the prevalence of TB in cattle herds and in surrounding badgers population due to important methodological differences. However, it would be also interesting to follow the relationship between the trends observed in some areas in cattle associated with disease control measures and the trend in the prevalence of these wild animal populations. Although the present dataset does not allow precise time comparison between P1 and P2 due to variations of sampling patterns and method for analyses, the ongoing surveillance may contribute to constitute consistent time series that may be analyzed for that concern. Nevertheless, in Côte-d'Or (area 2), if we considered that the apparent prevalence in P1 is underestimated because of the average sensitivity of the culture compared to that of the PCR, one can hypothesize that the prevalence has decreased in badgers from P1 to P2. In Dordogne/Charente (area 3), where both event-based and targeted surveillance in badgers have been effective, we observe that badgers collected by event-based surveillance (mainly road-killed badgers) were more infected than those trapped. This could be explained by a lower vigilance of infected badgers and therefore increased collisions with vehicles. Moreover, movements of infected badgers are higher (48) and these infected badgers occupy larger home ranges (49, 50). These elements point to a greater probability of detecting infection by collecting road-killed individuals than by trapping. Finally, we observed a higher prevalence in male than in female badgers, which corroborates several studies (51, 52). This has been interpreted as an influence of the aggressive behavior of males for the defense of the territories, and the attendance of several social groups during the rut period, resulting in a higher rate of infection in male badgers (52). Conclusion The implementation of a wide and important surveillance system as Sylvatub relies on the involvement, at the national or departmental level, of the main organizations involved in wildlife surveillance and field volunteers without whom this surveillance would not be possible. The detection of numerous cases of TB in free-ranging wildlife occurs in areas of cattle outbreaks with the same profile of M. bovis strains showing evidence that, in main endemic regions of France, TB circulates between cattle and wildlife. The current risk is that complex reservoirs of M. bovis including one or more wild populations and the environment are locally constituted. It is also worrisome to note the increase in the number of areas in which infected badgers or wild boars are found, partly due to a better surveillance over time. However, prevalence observed in France in badgers and wild boars are lower than those observed in the UK and in Ireland for badgers or in Spain for wild boars, and only sporadic cases have been detected in red deer and roe deer. Wildlife surveillance contributes to the implementation of control strategies in wildlife and in cattle by allowing defining at-risk areas. It also allows adapting surveillance in cattle keeping in mind the multi-host aspect of the disease as well as targeting prevention actions and to follow their long-term efficiency. This information, complemented by scientific investigations and researches, are needed for conducting biosecurity measures in wildlife (control of artificial feeding, management of hunting waste, banning game release, wildlife populations reduction in highly infected TB areas), and in livestock (management of water points, protection of the food and barns for example). Convinced that wildlife can be an additional local factor of TB spread and maintenance, the French ministry in charge of agriculture has decided to make Sylvatub sustainable. In parallel, evolvement of sampling strategies have been discussed in the aim to improve surveillance. In buffer areas, targeted surveillance will be replaced by M bovis detection in road-killed badgers. Another main development will concern wild boar in at-risk areas: serological testing for the detection of antibodies directed against M. bovis have been proposed as suitable tools for TB screening in wild boar populations (18, 53). ELISA method has been tested in comParison to PCR and culture in different areas in France with encouraging results (Richomme and Boschiroli, personal communication). It will be used as an alternative method to monitor the M. bovis exposure level in wild boars in the next years. Ethics Statement Samples were collected from animals trapped with appropriate permits, hunted legally during the hunting season with appropriate permits, shot legally because of severe debilitation, or found dead. All the samples included in this study were obtained from animals analyzed within an official context relating to TB surveillance in free-ranging wildlife. All sampling procedures complied with national and European regulations, and no specific ethics approval was therefore required. Author Contributions JH, AF, ÉR, CR, M-LB, ÉF, LC, FC, IT, SP, and PH: Sylvatub conception and monitoring; ÉR: Data analysis; ÉR, M-LB, CR, and SD: Paper writing; CR, M-LB, SD, JH, ÉF, AF, LC, PJ, IT, SP, PH, and FC: Manuscript critical revision. Funding Samples collection and analysis were funded by the DGAL. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Acknowledgments The authors would like to thank the local state veterinary services, the local hunting federations, the local services of the National Game Hunting and Wildlife Agency, the local laboratories for analysis, the local Animal Health Defense Associations, and Julie Rivière, the first coordinator of the Sylvatub system from 2011 to 2012. We are grateful to all the trappers and their associations, Pest control officers and their associations and hunters of wild ungulates without whom the surveillance could not have taken place. Thank to Craig Stevens for his very useful comments on this article and his careful reading. 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(2011) 23:77–83. doi: 10.1177/104063871102300111 PubMed Abstract | CrossRef Full Text | Google Scholar Keywords: bovine tuberculosis, Mycobacterium bovis, surveillance, wildlife, badger, wild boar, France Citation: Réveillaud É, Desvaux S, Boschiroli M-L, Hars J, Faure É, Fediaevsky A, Cavalerie L, Chevalier F, Jabert P, Poliak S, Tourette I, Hendrikx P and Richomme C (2018) Infection of Wildlife by Mycobacterium bovis in France Assessment Through a National Surveillance System, Sylvatub. Front. Vet. Sci. 5:262. doi: 10.3389/fvets.2018.00262 Received: 12 July 2018; Accepted: 02 October 2018; Published: 30 October 2018. Edited by: Daniel J. O'Brien, Michigan Department of Natural Resources, United States Reviewed by: Christian Menge, Friedrich Loeffler Institut, Germany Carol Geralyn Chitko-McKown, U.S. Meat Animal Research Center (ARS-USDA), United States Copyright © 2018 Réveillaud, Desvaux, Boschiroli, Hars, Faure, Fediaevsky, Cavalerie, Chevalier, Jabert, Poliak, Tourette, Hendrikx and Richomme. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Stéphanie Desvaux, stephanie.desvaux@oncfs.gouv.fr †Present Address: Édouard Réveillaud, Regional Directorate for Food of Nouvelle-Aquitaine, Limoges, France Alexandre Fediaevsky, DG Health and Food Safety, European Commission, Brussels, Belgium Pascal Hendrikx, Unit of Epidemiology and Support to Surveillance, Lyon, France

Review: Roles of Prebiotics in Intestinal Ecosystem of Broilers

REVIEW ARTICLE Front. Vet. Sci., 30 October 2018 | https://doi.org/10.3389/fvets.2018.00245 Po-Yun Teng and Woo Kyun Kim* Department of Poultry Science, University of Georgia, Athens, GA, United States In recent years, prebiotics have been considered as potential alternatives to antibiotics. Mechanisms by which prebiotics modulate the ecosystem of the gut include alternation of the intestinal microbiota, improvement of the epithelium, and stimulation of the immune system. It is suggested that the administration of prebiotics not only influences these aspects but also regulates the interaction between the host and the intestinal microbiota comprehensively. In this review, we will discuss how each prebiotic ameliorates the ecosystem by direct or indirect mechanisms. Emphasis will be placed on the effects of prebiotics, including mannan oligosaccharides, β-glucans, and fructans, on the interaction between the intestinal microbiota, gut integrity, and the immunity of broilers. We will highlight how the prebiotics modulate microbial community and regulate production of cytokines and antibodies, improving gut development and the overall broiler health. Understanding the cross talk between prebiotics and the intestinal ecosystem may provide us with novel insights and strategies for preventing pathogen invasion and improving health and productivity of broilers. However, further studies need to be conducted to identify the appropriate dosages and better resources of prebiotics for refinement of administration, as well as to elucidate the unknown mechanisms of action. Introduction Since the use of antibiotic growth promoters was banned by the EU on January 1st, 2006, several feed additives have been studied as alternatives to antibiotics, such as probiotics, prebiotics, synbiotics, and herbal medicines (1). Among these feed additives, prebiotics have been studied and supplemented broadly into broiler diets in recent years. Gibson and Roberfroid (2) defined a prebiotic compound as a non-digestible food ingredient utilized by intestinal microbiota. It beneficially affects the host by selectively stimulating the growth and/or activity of one or a limited number of bacteria in the intestinal tract, consequently improving gut health and hosts' intestinal microbial balance. Gibson et al. (3) revised the definition and defined a prebiotic as a selectively fermented ingredient that allows specific changes in the composition and/or activity in the intestinal microbiota that confers benefits upon the host's well-being and health. Some researchers also confined prebiotics to indigestible oligosaccharides (4). Ideal characteristics of prebiotics were described by Patterson and Burkholder (5): (1) prebiotics should not be hydrolyzed by animal gastrointestinal enzymes, (2) prebiotics cannot be absorbed directly by cells in the gastrointestinal tracks, (3) prebiotics selectively enrich one or limited numbers of beneficial bacteria, (4) prebiotics alter the intestinal microbiota and their activities, and (5) prebiotics ameliorate luminal or systemic immunity against pathogen invasion. The ecosystem of the gut is composed of three crucial elements: (1) microbial community, (2) intestinal epithelial cells, and (3) immune system (6). Generally, prebiotics can be fermented by health-promoting bacteria in the intestine, producing lactic acid, short-chain fatty acid (SCFA), or some antibacterial substances, such as bacteriocine against pathogenic species (7). These products may not only benefit the intestinal microbial structure but also improve the integrity of intestinal epithelial cells, which further increase the absorption of nutrients and enhance the growth performance of animals (8). Intestinal microbiota are influenced by various factors, including diet, gender, background genotype, housing environment, litter, and also age of birds (9). These factors can alter the abundance of dominant bacterial phyla and families in each part of the intestine. For instance, gut microbiota in young chickens changed rapidly with increase of age. Clostridiaeae and Enterobacteriaceae are two dominant families in the ileum of 7 day-old chickens, whereas Lactobacillaceae and Clostridiacea represent the common families in the ileum of 35 day-old birds (9). However, the balance of intestinal microbiota is alterable. Application of prebiotics in diets could establish a healthy microbial community in the intestine of young broilers by enhancing the abundance of Lactobacilli and Bifidobacteria and reducing the titers of Coliform (10, 11). Furthermore, the modulation of intestinal microbiota is associated with immune responses. On the one hand, inhibiting pathogen colonization by prebiotics can decrease detrimental molecules produced by pathogenic bacteria, which have been known as exogenous signals (12). These signals are also called pathogen-associated molecular patterns (PAMPs). The PAMPs can be recognized by pattern recognition receptors (PRR), including toll-like receptors (TLRs) and NOD-like receptors (NLRs), which are expressed on the surface of sentinel cells (13). Once PRRs recognize PAMPs, sentinel cells, such as epithelial cells, macrophages, mast cells, and dendritic cells, are activated, producing cytokines for the regulation of further innate immune responses. On the other hand, prebiotics can act as non-pathogenic antigens themselves. They can be recognized by receptors of immune cells, which consequently modulate host immunity beneficially. Various prebiotics are composed of diverse sugar units. Therefore, each prebiotic may influence the animals differently. Here, we reviewed studies of broilers that discuss the effects of prebiotics on their underlying mechanisms of action. We will discuss the direct or indirect mechanisms by which prebiotics ameliorated the ecosystem of the chicken gut. Emphasis will be placed on the impacts of mannan oligosaccharides, β-glucans, and fructans on the interaction between the intestinal microbiota, immunity, and the integrity of the epithelial cells (Figures 1–3). FIGURE 1 www.frontiersin.org Figure 1. The potential mechanisms of action of MOS on improving immunity and inhibiting pathogen colonization. FIGURE 2 www.frontiersin.org Figure 2. The potential mechanisms of action of fructans on improving immunity and inhibiting pathogen colonization. FIGURE 3 www.frontiersin.org Figure 3. The potential mechanisms of action of β-glucan on improving immunity and inhibiting pathogen colonization. Mannan Oligosaccharides (MOS) Most of the mannan oligosaccharide (MOS) products are derived from yeast cell walls (Saccharomyces cerevisiae) and are rich in mannoproteins (12.5%), mannan (30%), and glucan (30%) (14, 15). Mannan oligosaccharides are known for their ability to bind pathogenic bacteria, which possess type-1 fimbriae, such as E. coli and Salmonella species (16). By blocking bacterial lectin, MOS could reduce colonization of these pathogens in the intestine of animals (17). Previous studies indicated that supplementation of MOS from 0.08 to 0.5% could alter cecal microbial community composition by increasing total anaerobic bacteria, Lactobacillus and Bifidobacterium, and decreasing Salmonella, E. coli, Clostridium perfringens, and Campylobacter (14, 16, 18–23). Apart from its effects on cecal microbiota, MOS also improved microbial community in other sections of the intestine, including the jejunum, the ileum, the jejunal mucosa, the ileal mucosa, and the ileocecal junction (11, 22, 24–26). It is interesting to note that MOS increased cecal Bacteroidetes in 7 and 35 day-old broilers (23, 27). Genus Bacteroides have been known for their strong metabolic activity. They can efficiently ferment indigestible polysaccharides to SCFA and, consequently, improve nutrient absorption and protect the host from pathogen infection (28). In previous studies, shown in Table 1, Lactobacillus species were the main species influenced by MOS. Mannan oligosaccharides increased the prevalence of ileal L. acetotolerans, L. delbrueckii subsp. lactis, L. sakei subsp. sakei. and cecal L. ingluviei, L. mucosae, L. salivarius, and L. crispatus (23, 29). Among these Lactobacillus species, L. crispatus was reported to have anti-E. coli and anti-Salmonella activities, whereas L. salivarius was mentioned to have the ability to limit Salmonella colonization (30, 31). The anti-pathogenic characteristics of Lactobacillus may be the reason why MOS reduced the numbers of E. coli or Salmonella in the intestine, ameliorating bacterial infection in pathogen-challenged broilers (14, 16, 19). TABLE 1 www.frontiersin.org Table 1. Effects of mannan oligosaccharides on intestinal microbiota of broilers. In addition, higher levels of intestinal Lactobacillus in birds fed with MOS may further result in the improvement of gut health status. Mannan oligosaccharides have been reported to increase villus height and surface area, decrease crypt depth, induce numbers of sulphated-acidic goblet cells, and upregulate gene expression of MUC, which is related to mucin secretion (10, 11, 14, 32–35) (Table 2). It has been reported that sulphated-acidic goblet cells are less degradable by the pathogen's glycosides (43, 44). Therefore, they can provide stronger protection against pathogens for the host. Similarly, Cheled-Shoval et al. (36) reported that in ovo administration of MOS enhanced villus area and proliferation of goblet cells. The greater numbers of goblet cells were able to increase the gene expression of MUC, synthesizing and secreting more mucin, which plays an important role as the first line of defense. Mucin can trap pathogens or impede them from invading epithelial cells (45). Thus, it is hypothesized that MOS establishes a bidirectional interaction: the increase of Lactobacillus counts may improve intestinal development, whereas mucin produced by goblet cells can conversely limit attachment of pathogens to epithelial cells. TABLE 2 www.frontiersin.org Table 2. Effects of prebiotics on intestinal morphology of broilers. The effects of MOS on immunity of broilers are presented in Table 3. TLR4 and TLR2 were upregulated in the ileum or cecal tonsils by 0.2% MOS supplementation (50). It indicated that MOS could be recognized by both TLR4 and TLR2. Similar to mammalian TLR4, chicken TLR4 (chTLR4) mRNA has been found in a wide range of cells, particularly in macrophages and heterophils (61). TLR4 is a receptor that recognizes lipopolysaccharide (LPS) in mammals. After recognizing LPS, immune cells could produce high levels of nitric oxide and pro-inflammatory cytokines against pathogenic bacteria. Thus, it was suggested that reducing the exposure of LPS from E. coli by MOS could downregulate gene expression of chTLR4 and inhibit pro-inflammatory immunity (50). However, molecules of MOS can be recognized by TLR4 as well. It was reported that MOS may act as a pro-inflammatory factor that upregulates TLR4 gene expression and induces innate immune responses (62). TABLE 3 www.frontiersin.org Table 3. Effects of mannan oligosaccharides, β-glucan, and fructans on immune responses of broilers. However, chicken TLR2 (chTLR2) has approximately 50% amino acid identity to mammal TLR2, which can recognize a broad variety of PAMPs, including lipoproteins, aribinomannan, and peptidoglycan fugal zymosan (61). TLR2 may recognize MOS as well, which leads to the pro-inflammatory cytokines' cascade (63). A previous study demonstrated that supplementation of 0.2% MOS in broiler diets enhances ileal gene expression of interleukin-12 (IL-12) and interferon-γ (IFN-γ) (50). Interleukin-12 is a cytokine that stimulates T-helper type-1 cells (Th1 cells) and triggers IFN-γ to induce proliferation and cytotoxicity of immune cells, such as T cells, natural killer (NK) cells, and macrophages (12). Apart from the upregulation of innate immunity, MOS can impact humoral immune responses by acting as adjuvant of vaccines to enhance antibody titers. Previous studies have shown that MOS can strengthen antibody titers against sheep red blood cells, infectious bursal disease virus, Newcastle disease virus, and avian influenza virus (47–49). On the contrary, some reports have noted that antibody titers against Newcastle disease virus and infectious bursal disease virus failed to increase in chickens with MOS supplementation (64, 65). This discrepancy among studies may be based on whether or not broilers are infected with pathogens or the variations in MOS sources and environmental conditions (51). The effects of MOS on intestinal microbiota have been reported broadly. Most of the MOS additions can significantly improve microbial community composition. However, there has been limited research on the impacts of MOS on mechanisms of immune responses in broilers. Although previous studies have found some auspicious results, further research is necessary to determine further antibody titers and gene expression of TLR or cytokines in order to elucidate how MOS improves the broiler's immunity. β-glucan β-glucan is a prebiotic derived from yeast or fungal cell walls. This long-chain polysaccharide is composed of D-glucose monomers with linkages of β-glycosidic 1-3 bonds, and its side-chains are linked by the 1–6 bonds. β-glucan can be recognized by receptors on sentinel cells, triggering production of cytokines and proliferation of lymphocytes (66). Lymphocytes are classified into three major types. The first type is NK cells, which play an important role in innate immunity. The second type is T cells, which regulate adaptive immunity. The third type is B cells, which produce antibodies against antigens. All types of lymphocytes can be modulated by β-glucan. The influences on immune responses of broilers are shown in Table 3. Macrophages may be one of the sentinel cells that recognize β-glucan in the animal intestine. When macrophages are activated by β-glucan, they produce inducible nitric oxide synthase (iNOS) (56), an enzyme that produces large amounts of nitric oxide. Reacting with superoxide anion, nitric oxide is oxidized to a highly-toxic nitrogen dioxide radical that can kill a wide range of invading pathogens directly or block their DNA synthesis (12, 52, 58). Moreover, β-glucan exposure also triggers macrophage proliferation, enhances macrophage phagocytic ability, and induces macrophage-modulating gene expression of interleukin-1 (IL-1), interleukin-18 (IL-18), and tumor necrosis factor-α (TNF-α) (38, 52). Increasing TNF-α in birds fed with β-glucan may stimulate the incidence of CD8+ lymphocyte, a receptor expressed only on the cytotoxic T cell (Tc) (52, 54). Thus, it is hypothesized that β-glucans can regulate innate immune response by inducing proliferation of Tc cells to attack pathogen-infected cells. Heterophils, recruited by sentinel cells, are the major granulocytes in most birds and work in a manner similar to neutrophils in mammals. Lowry et al. (53) showed the increases of heterophil phagocytosis in broilers fed with β-glucan, including enhancing the percentage of heterophils containing Salmonella enterica, mean numbers of Salmonella enterica per heterophil, and phagocytic index. One reasonable explanation that has been proposed is that the dectin-1 receptor involved in β-glucan recognition on the surface of macrophages may also be present on the surface of heterophils (67). Furthermore, heterophils stimulated by β-glucan can release nitric oxide and kill Salmonella enterica, resulting in the reduction of pathogenic organ invasion (53). Apart from heterophils, β-glucan receptors are also present on NK cells in humans (68). Therefore, activating NK cells by β-glucan may be another way to improve immune responses in broilers. On the contrary, Cox et al. (56) indicated that β-glucan could be an anti-inflammatory immunomodulator inhibiting interleukin-8 (IL-8) gene expression. Interleukin-8 is a cytokine produced by macrophages, which can recruit heterophiles to phagocytose pathogens at the site of inflammation (12). The inconsistent results may be attributed to whether or not the birds were challenged by pathogens. In a pathogen-challenging situation, pro-inflammatory immune responses may be enhanced by β-glucan supplementation, whereas in normal circumstances, β-glucan may be an anti-inflammatory modulator. It was reported that the inclusion of β-glucan in diets could regulate the gene expression of antimicrobial peptides (AMPs) (57). Cathelicidins (Cath), avian β-defensins (AvBDs), and liver-expressed antimicrobial peptides (LEAP) are three major families of AMPs, which are expressed by the lung, intestine, immune, and reproductive organs in chickens (57). Antimicrobial peptides can penetrate the membrane of fungi or bacteria, leading to the death of pathogens. Among AMPs, Cath-1 and Cath-2 proteins have been shown to posses the capacity to bind to LPS, inhibiting LPS-mediated pro-inflammatory immune responses (61). On the other hand, AvBDs expressed in heterophils and the mucosal surface of the intestinal and respiratory tracts can damage pathogens, like Staphyloccocus aureas, E. coli, Candida albicans, S. Enteritidis, S. Typhimurium, Listeria monocytogenes, and Campylobacter jejuni (61). Shao et al. (57) reported that the gene expression of Cath-1, Cath-2, AvBD-1, AvBD-2, AvBD-4, AvBD-6, AvBD-9, and LEAP-2 were increased in Salmonella-challenged broilers with β-glucan addition. On the contrary, the same study showed that β-glucan reduced Cath-1, AvBD-4, and AvBD-9 in the spleen of birds without pathogen challenge. It could be concluded that if broilers were under pathogen infection, β-glucan would exhibit a strong protection against Salmonella and other pathogens in broilers. After recognizing β-glucan, sentinel cells secrete cytokines that activate Th1 or Th2 cells. The Th1 cells drive the type-1 pathway attack against intracellular pathogens, whereas Th2 cells dominate the type-2 pathway triggering humoral immunity to upregulate antibody production (69). Although Th1 and Th2 cells could release cytokines to cross-inhibit each other, type-1 and type-2 pathways could both be triggered by β-glucan. In type-1 pathways, interleukin-12 (IL-12), produced by macrophages, is a key cytokine that enhances the proliferation of Th1 cells and the production of IFN-γ (12). Interferon-γ further reinforces with IL-18 in order to trigger the activation of Th1 cells and produce additional IFN-γ and IL-2 for the activation of NK cells, stimulation of macrophages and Tc cells, and inhibition against Th2 cells (12). Previous studies reported that β-glucan upregulates the gene expression of IL-2, IL-18, and IFN-γ (52, 54). Additionally, levels of the cytokines interleukin-4 (IL-4) and interleukin-13 involved in type-2 cell pathways are downregulated by β-glucan as well (56). These outcomes support the hypothesis that β-glucan can stimulate the type-1 pathway and inhibit the type-2 pathway. However, gene expression of IL-1 involved in the type-2 pathway could also be induced by β-glucan (52). Increasing IL-1 found in abdominal exudate cell macrophages can activate Th2 cells and switch on the type-2 pathway. Once activated, Th2 cells release other cytokines to initiate the subsequent anti-inflammatory immune responses. For instance, IL-4 can suppress Th1 cells' activation, stimulate B cells' growth and differentiation, and activate mast cells to produce immunoglobulins (12). Owing to the suppression of Th1 cells, gene expression of IFN-γ was downregulated in duodenum, jejunum, and ileumthe duodenum, the jejunum, and the ileum by β-glucan in Eimeria-challenged broilers (38). On the other hand, enhancing immunoglobulins, including IgG and sIgA, in broilers were found by Zhang et al. (54). This is evidence showing that the type-2 pathway can be upregulated by β-glucan. Shao et al. (57) also reported that anti-Salmonella specific IgA levels in the jejunum and anti-Salmonella specific IgG levels in the serum were increased in birds fed with β-glucan. Similarly, Shao et al. (37) demonstrated that β-glucan could protect intestinal barrier function in Salmonella-challenged birds by increasing the amount of goblet cells and IgA-secreting cells, which enhance the sIgA production. sIgA is an important immunoglobulin that serves as the first line of defense (70). There are three major mechanisms of sIgA to protect the integrity of gut lining from pathogenic invasion (71). Firstly, sIgA interacts with non-pathogenic bacteria and epithelium, which consequently strengthens the tight junctions between intestinal epithelial cells and inhibits nuclear translocation of NF-κB (70). A previous study also confirmed that β-glucan enhanced the production of sIgA to ameliorate the damage of tight junction in the jejunum caused by Salmonella (37). Secondly, immune complexes that interact with sIgA are involved in the downregulation of gene expression of pro-inflammatory cytokines that include IFN-γ, TNF-α, and interleukin-6 (IL-6) (70). Thirdly, sIgA blocks pathogens within mucin, selecting and maintaining a favorable balance of microbiota in the intestine (70). Shao et al. (37) showed that increased sIgA by β-glucan was associated with the reduction of cecal Salmonella colonization and liver invasion. In summary, β-glucan affects the broiler's immunity via either the type-1 or the type-2 pathway. The conflicting results among different studies may be attributed to the different dosages offered, different ages of the birds used, different parts of the tissue examined, or numerous resources of the β-glucan supplemented. Inconsistent results have also been demonstrated in other animals. For example, cytokines involved in the type-2 pathway of immune responses were downregulated by β-glucan in humans (72) but upregulated in mice (73). Therefore, additional investigation is needed to understand fully the effects of β-glucan on immune responses of broilers. Fructans Fructans, commonly extracted from different plants, hydrolyzed from polysaccharides, or produced by microorganism, have been administered recently in broiler diets. Fructans are classified into three distinct types: the inulin group, the levan group, and the branched group. Firstly, the inulin group, also known as fructooligosaccharides (FOS) can be divided into different categories based on degrees of polymerization (DP): Inulin, normally extracted from chicory roots (Cichorium intybus L.), consists of a DP of 3 to 60, and Oligofructose (OF), which can be generated by partial hydrolysis of inulin, enzymatic conversion of sucrose, or lactose, contains a DP of 2 to 10 (74, 75). Most of the inulin group can be found in plants, which comprise oligosaccharides with β-2,1 fructosyl-fructose linkage with a glucose terminal unit. Secondly, the levan group is another group of fructans, which are mostly linked by β-2,6 fructosyl-fructose bonds. Lastly, fructans, which belong to the branched group, contain both β-2,1 fructosyl-fructose and β-2,6 fructosyl-fructose bonds in fair amounts (76). It is the β-glycosidic bond in fructans that resists their breakdown by digestive enzymes in poultry and enhances the population of beneficial bacteria, such as Bifidobacteria and Lactobacilli, and suppresses levels of pathogenic bacteria, such as Clostridium pefringens and E. coli, in the intestine of broilers (25, 40, 77). Saminathan et al. ( 78) evaluated the utilization of different oligosaccharides by 11 Lactobacillus species isolated from the gastrointestinal tract of chickens. This in vitro report showed that FOS were utilized by Lactobacillus more efficiently than MOS. The high availability of FOS may be associated with specific enzymatic activity and the oligosaccharide transport system of Lactobacillus species (79, 80). However, the intestinal microbiota of a broiler is far more complex than those in in vitro trials. The prebiotics may be fermented not only by Lactobacillus species but also by other microorganisms in the gastrointestinal tracts of animals. Thus, it cannot be assured that the utilization of FOS and MOS in in vitro trials is as efficient as in in vivo studies. In addition, the more DP increased, the more residual FOS remained after fermentation by Bifidobacteria (81). A previous study indicated that almost 55 Bifidobacteria preferred to grow on short-chain FOS rather than long-chain FOS (75). Bifidobacteria could also ferment short-chain FOS to produce more acetic acid and lactic acid compared with long-chain FOS within 24 h (81). Similarly, Perrin et al. (82) reported that the population of Bifidobacteria and Lactobacilli increased earlier in fecal cultures containing OF instead of inulin. However, an increase in the production of formic acid, acetic acid, and lactic acid and a decrease in numbers of E. coli group and Cluster I clostridia were both observed in cultures containing OF or inulin after 24-h fermentation (82). The same research group also pointed out that butyric acid might be the major product in the inulin group, whereas more acetic acid and lactate acid could be produced from OF (75). Long-chain fructans, which are degraded slowly in the animal gut, can pass through the small intestine and be fermented in the distal regions of the intestine. Therefore, the inulin group with higher DP might not affect the microbiota in the jejunum significantly (83), but, instead it might alter microbial structure and increase the concentration of SCFA or lactic acid in the ceca of broilers. Effects of FOS on intestinal microbiota are shown in Table 4. Park et al. (85) demonstrated that FOS increased the Shannon diversity of intestinal microbiome compared with the control treatment. Moreover, similar to in vitro results, Bifidobacteria and Lactobacillus are two major beneficial bacteria that were increased in broilers and hens fed with fructans (40, 41, 76, 84, 88). Bifidobacteria and Lactobacillus not only produced extracellular enzymes to degrade FOS but also competed with other species of intestinal microorganisms and suppressed the growth of pathogenic bacteria (75). For instance, Campylobacter titers in the ceca and large intestine were decreased in broilers fed with FOS (84). Regardless of the supplementation of long-chain FOS or short-chain FOS, a reduction in titers of C. perfringens was observed in the ileocecal junction or ceca of broilers (20, 25, 76). Similarly, colonization of cecal C. perfringens and Salmonella typhimurium was decreased by FOS or FOS combined with competitive exclusion products in E. coli or Salmonella- Typhimurium-challenged birds, respectively (10, 87). Additionally, diets containing different concentrations of FOS (from 0.25 to 1%) could decrease cecal E. coli and Salmonella in broilers (25, 40, 76, 84, 86). Besides the prevention of Salmonella colonization in the ceca of broilers, previous reports also demonstrated that FOS-supplemented diets decreased ovary, liver, and cecal Salmonella enteritidis in laying hens (89, 90). The reduction of these pathogenic bacteria might be attributed to cecal SCFA and lactic acid. Same as in vitro results, the concentration of cecal butyric acid and lactic acid was significantly higher in broilers fed with inulin (41, 83). Donalson et al. (89) also showed that 0.75 or 0.375% of FOS combined with alfalfa molt diets could increase the concentration of cecal isobutyric acid in hens. Short-chain fatty acids are important fuels in the intestine, and butyrate is the major one that is metabolized by epithelial cells, providing energy for the growth of mucosal epithelium (91). It is suggested that higher concentrations of butyric acid are associated with the improvement of mucosal structure. Previous studies reported that microvillus height in the jejunum and ileum and the ratio of villus to crypt depth in the ceca were increased by FOS (40, 41). Bogucka et al. (92) also reported that in ovo injection of inulin increased villus height in broilers at the first day after hatching. In addition, the use of inulin could increase jejunal mucin mRNA expression to produce more mucin, protecting intestinal epithelial cells in broilers (39). By improving intestinal morphology, FOS could further enhance activities of protease and amylase and nutrient absorption, leading to better growth performance (40). TABLE 4 www.frontiersin.org Table 4. Effects of fructans on intestinal microbiota of broilers. However, adding high levels of fructans could result in negative impacts on broilers. Rapid fermentation by microbes in the intestine could produce too much SCFA, which damage intestinal mucosal barriers and increase intestinal permeability, consequently causing pathogen invasion, diarrhea, and poor growth performance (93, 94). Xu et al. (40) demonstrated that the addition of 0.2 or 0.4% of FOS in broiler diets could improve FCR and change cecal microbiota, but the supplementation of 0.8% of FOS had no significant differences compared with control treatment. It has been suggested that the supplementation of FOS above 0.5% is excessive; a previous report mentioned that birds fed with 0.5% FOS showed poorer growth performance and less intestinal Lactobacillus but higher titers of E. coli and C. perfringens compared with 0.25% FOS treatment (25). Furthermore, Biggs et al. (20) even showed that MEn and amino acid digestibility were reduced by 8% short-chain FOS or inulin addition. Fructans improved the immune responses of gut-associated lymphoid tissue (GALT) and the systemic immune system through three major mechanisms. Firstly, increasing the levels of Bifidobacteria by fructans could modulate the production of cytokines or antibodies. Secondly, leukocytes could be activated after their receptors respond to fructans' metabolites, such as SCFA. Thirdly, fructans could be directly recognized by carbohydrate receptors on the surface of immune cells (95). Huang et al. (39) reported that inulin reduced the levels of IL-6 and IFN-γ, increased IgA, and tended to increase the ratio of CD4+/CD8+ cells in the ileum of broilers. Moreover, Janardhana et al. (46) found that FOS could lead to systemic immune responses by increasing the levels of plasma antibody titers of IgG and IgM. Similarly, primary antibody titers against sheep red blood cells increased in broilers fed with FOS, but antibody titers in the secondary immune response were not influenced by FOS (59). Likewise, FOS increased IgA+ cells and upregulated TLR-4 and IFN-γ in the ileum of laying hens (90). Interestingly, there is a hypothesis that fructans might modulate the development of the immune system during embryogenesis. In ovo administration of inulin (d 12) downregulated the gene expression of IL-4, IL-12p40, IL-18, CD80, and interferon-β in the cecal tonsils of broilers on day 35 after hatching (60). Furthermore, in ovo injection of inulin had no adverse effect on GALT development but stimulated more colonization of lymphoid tissue by T cells in the cecal tonsil of broilers (96). To our knowledge, there are only a few studies that evaluated the in ovo administration of prebiotics. Further research is needed to understand what causes the different results between in ovo administration and direct-fed supplementation of fructans in broilers. It could be concluded that owing to the various fructans groups and DP, supplementation of fructans in diets might have affected broilers inconsistently. However, in a general review, fructans could modulate intestinal microorganisms, levels of intestinal SCFA, mucosal morphology, and generate immune responses. Other Prebiotics Besides the three major prebiotics, MOS, β-glucan, and fructans, other oligosaccharides have been evaluated and considered as potential prebiotics, including chitosan oligosaccharides (COS), galacto-oligosaccharides (GOS), galactoglucomannan oligosaccharide (GGMO), and xylo-oligosaccharides (XOS). Chitosan Oligosaccharides (COS) Extracted from chitin, COS contain 2–10 sugar units of N-acetyl glucosamine with 1–4 β-linkages. It has been reported that the supplementation of COS in broiler diets could modulate immune responses and enhance nutrient digestibility and feed efficiency. Huang et al. (97) indicated that chicken with COS supplementation had higher weight of bursa of Fabricius and thymus, higher IgG, IgA, and IgM in serum and higher antibody titers against Newcastle disease vaccines. On the other hand, 0.01% of COS improved ileal digestibility of dry matter, energy, crude protein, and most of the amino acids in broilers (21 or 42 d) (98). The improved digestibility of nutrients was associated with better growth performance in the same study (98). However, supplementation of COS above 0.01% might be excessive because chickens fed with 0.015% COS had significantly less body weight than birds fed with 0.01% COS (98). Galacto-Oligosaccharides (GOS) Galacto-oligosaccharides, synthetic prebiotics with galactose with 1–4 or 1–6 β-linkages, are normally produced from lactose by the enzyme lactase with high galactosyltransferase activity (99). In ovo injection of GOS could increase body weight of broilers 34 days after hatching (100). Administration of GOS also influenced the intestinal microbiota. Park et al. (85) reported that GOS treatment exhibited higher levels of Alistipes genus, Lactobacillus intestinalis, and Faecalibacterium prausnitzii in the ceca of broilers compared with the control group. Although Biggs et al. (20) demonstrated that GOS had no effects on cecal Bifidobacteria and Lactobacillus population, it has been reported that the addition of GOS in broiler diets could increase counts of Bifidobacteria in feces (101). Moreover, broilers that received in ovo GOS injection also had higher concentrations of Bifidobacteria and Lactobacillus in feces (102). The author suggested that in ovo administration of GOS could replace prolonged water supplementation. Owing to the inconsistent results, future studies are needed to confirm the effects of GOS in modulating intestinal microbial structures and further affecting immune responses in broilers. Galactoglucomannan Oligosaccharides (GGMO) and Galactoglucomannan Oligosaccharides-Arabinoxylan (GGMO-AX) Galactoglucomannan oligosaccharides and galactoglucomannan oligosaccharides-arabinoxylan (GGMO-AX) are novel prebiotics extracted and processed from the wood chips of softwood trees (103). These oligosaccharides consist of mannose, glucose, and galactose monomers. An in vitro investigation showed that Lactobacillus could grow faster on GGMO than MOS (35). The same research also indicated that the supplementation of 0.2% GGMO in broiler diets could reduce colonization of Salmonella typhimurium in the ileum, ceca, and liver; as a consequence of clearing S. typhimurium infection, GGMO ameliorates intestinal morphology and growth performance compared with a Salmonella-challenged control treatment (35). The improvement might be attributed to the modulation of immune responses by GGMO. Faber et al. (104) reported that the Eimeria acervulina-challenged birds that received 4% GGMO-AX showed enhanced gene expression of pro-inflammatory cytokines, including IFN-γ, IL-1β, IL-6, and IL-12β, but also showed decreased levels of anti-inflammatory cytokines such as interleukin-15. Galactoglucomannan oligosaccharides-arabinoxylan might not only affect immune responses in broilers but also alter intestinal microbial population. It has been shown that the administration of 2% GGMO-AX increased counts of Bifidobactrium spp. in the ceca (104) and 4% GGMO-AX decreased the concentration of C. perfringens (105). Although the supplementation of GGMO-AX in high levels showed some positive effects on broilers, simultaneously, it could lead to poor growth performance (104). Therefore, further studies should evaluate the administration of GGMO or GGMO-AX in appropriate concentration to maintain growth performance and improve the health status of broilers at the same time. Xylo-Oligosaccharides (XOS) Xylo-oligosaccharides are oligosaccharides, which consist of xylose sugar units with β-linkages (42). Xylan, the main component of cereal fiber such as corn cobs, straws, hulls, and bran are the raw resources for XOS production (106). Xylan could be degraded to XOS by xylanase of fungi, steam, or diluted solutions of mineral acid (106). Similar to other prebiotics, XOS could improve growth performance, increase the intestinal villus height, increase the proportion of Lactobacillus, and enhance the levels of acetate, butyrate, and lactate in the ceca of broilers (42, 107, 108). It was suggested that XOS would improve humoral immunity in poultry. An increase in antibody titers against avian influenza H5N1 was observed in broilers by XOS addition (107). Furthermore, De Maesschalck et al. (42) speculated that XOS could lead to cross-feeding mechanisms between L. crispatus and Anaerostipes butyraticus in the gut of the broiler. Owing to XOS fermentation, L. crispatus produces lactate, which might be utilized by butyrate-producing bacteria that belong to members of Clostridium cluster XIVa. This hypothesis was further supported by the observation of increasing numbers of cecal Clostridium cluster XIVa and butyryl-CoA: acetate-CoA transferase, a marker indicating the butyrate-producing capacity of intestinal microbiota (42). As mentioned above, butyrate is a major energy source for intestinal epithelial cells. Apart from acting as an important fuel in the intestine, butyrate can stimulate MUC-2 gene expression, exert anti-inflammatory effects, and prevent necrotic enteritis from pathogenic infection (109–111). In summary, XOS supplementation would enhance cross-feeding mechanisms and produce butyrate, consequently leading to beneficial influences on broilers. In Ovo Injection Direct feeding and in ovo injection are two main strategies for applying prebiotics. Prebiotic can be administrated by injecting 0.2 ml aqueous solution into the air chamber of eggs on day 12 of embryonic incubation (112). In ovo injection of prebiotics can alter microbial community in embryonic guts, improve intestinal morphology, and directly promote robustness of both cellular and humoral immune responses in the GALTs of the neonate post hatching (96, 113, 114). The embryonic microbiota is different from the intestinal microbiota of post hatching and adult birds. The dominant bacterial phylum is Proteobacteria, followed by Firmicutes, Bacteroidetes, and Actinobacteria in the chicken embryos (115). In addition, the embryonic microbial community is altered during the development of the embryos. The 19-day-old embryos exhibited more microbial diversity than the 4-day-old embryos. The proportion of Proteobacteria decreased, whereas Firmicutes, Bacteroidetes, and Actinobacteria increased in the 19-day-old embryos compared with the 4-day-old embryos (115). Even though Proteobacteria decreased in the late embryonic development period, this phylum dominated in early-age birds until Firmicutes became prominent after 7 days post hatching (116). However, the embryonic microbiota could be contaminated by pathogens directly from the yolk, yolk membranes, albumen, shell membranes originating from the reproductive organs of laying hens, or indirectly from the egg shells. Pathogens such as Salmonella located in the albumen were able to migrate and penetrate the vitelline membrane and grow in the yolk (117). On the other hand, it was suggested that spore forming bacteria such as Clostridium tertium were capable of surviving the disinfection process and penetrating eggs, resulting in contamination (118). To avoid extensive pathogen infection, prebiotics were delivered in ovo, which is likely fermented by the indigenous embryonic microbiota, inhibiting pathogen proliferation and regulating gene expression of immune responses (119). Villaluenga et al. (120) reported that injection of raffinose at day 12 of embryonic incubation had the highest amounts of Bifidobacteria in the ceca of 2 day-old broilers. Additionally, they indicated that 8.815 mg per egg of raffinose delivered in ovo reduced embryo weight. A later research showed that 4.5 mg of raffinose that was delivered in ovo had no significant effects on body weight but enhanced gene expression of CD3 and ChB6, which are associated with the activity of T cells and B cells (114). Moreover, villus height and villus height to crypt depth ratio of post hatching birds increased linearly with higher dosages of raffinose (114). In ovo injection of inulin and GOS also increased villus height in the jejunum of 1-day-old chickens (92). Moreover, administration of GOS in ovo showed differential gene expression in the ceca related to lymphocyte proliferation, activation, and differentiation and cytokine production (119). This study pointed out that GZMA (Granzyme A), a cytotoxic T cell-specific gene, was upregulated in the cecal tonsil of birds delivered with GOS in ovo. Similarly, other research has also demonstrated that GOS increased helper T cells in the cecal tonsil and B cells in the bursa of Fabricius (96). Furthermore, beta inhibin and lectin galactoside-binding soluble 3, which are related to regulation of T cell and innate immunity, were upregulated by GOS. On the other hand, GOS also downregulated the SERPING1 gene, which could inhibit part of the complement cascade system (119). It was suggested that the in ovo injection of GOS might not only regulate intestinal innate and adaptive immune system but also modulate gene expression of nutrient digestion and transportation. Firstly, chicken injected with GOS in ovo exhibited higher levels of sodium-dependent glucose co-transporters in the intestine, which are related to the absorption of monosaccharides (119). Secondly, birds delivered with GOS in ovo showed increased amylase and trypsin activity of the pancreas on embryonic day 21 and day 7 post hatching respectively (100). These studies led us to a conclusion that in ovo injection of prebiotics could affect the ecosystem of broilers, but, to our knowledge, little research has compared the difference between the direct-fed method and in ovo injection. A study reported that injection of galacto-oligosaccharides into eggs could increase Bifidobacteria and Lactobacillus in the feces of broilers. Though the author suggested that in ovo injection could replace prolonged supplementation via water system (102), more studies are needed to compare these two different approaches on the application of prebiotics. Conclusion The interaction between epithelium, microbiota, and immunity in animal gut is complicated. Recent data have demonstrated that prebiotics potentially alter the interaction between the host and gut microbiota and improve the health status of broilers. However, the interaction is sometimes induced by certain prebiotics or host species. Therefore, it is inevitable that prebiotics showed variable effects on animals. Still, most prebiotics can be fermented by beneficial bacteria, and the increased levels of Lactobacillus and Bifidobacteria or their metabolites may inhibit pathogen colonization and communicate with epithelial cells and immune cells. By improving gut environment or immune responses, prebiotics further provide resistance to pathogens and maintain efficient production. In addition, some prebiotics can be recognized by sentinel cells directly, triggering cytokines' cascade, which results in the upregulation of innate or humoral immunity. Although previous studies have discovered some mechanisms that participate in the cross talk between prebiotics and the ecosystem of the gut, there are still several hypotheses, which shall be confirmed in the future. In this context, administration of prebiotics presents tremendous influences on the broilers' gut health by the modulation of the gut microbial community and the interaction between the host immune system and gut microbiota. It is suggested that prebiotics delivered in ovo or fed directly can act as alternatives to antibiotics because of the significant improvement of microbial community, intestinal integrity, and immunity of the host. Author Contributions P-YT reviewed papers related to the topics and wrote the manuscript. WK reviewed papers related to the topic, gave directions and ideas to P-YT, and reviewed and revised the manuscript. 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Edited by: Rajesh Jha, University of Hawaii at Manoa, United States Reviewed by: Maria Siwek, University of Science and Technology (UTP), Poland Akshat Goel, Central Avian Research Institute (ICAR), India Copyright © 2018 Teng and Kim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Woo Kyun Kim, wkkim@uga.edu