Infections with Tuberculosis (TB)-causing agents of the Mycobacterium tuberculosis complex threaten human, livestock, and wildlife health globally due to the high capacity to cross trans-species boundaries. Tuberculosis is a cryptic disease characterized by prolonged, sometimes lifelong subclinical infections, complicating disease monitoring. Consequently, our understanding of infection risk, disease progression, and mortality across species affected by TB remains limited. The TB agent Mycobacterium suricattae was first recorded in the late 1990s in a wild population of meerkats inhabiting the Kalahari in South Africa and has since spread considerably, becoming a common cause of meerkat mortality. This offers an opportunity to document the epidemiology of naturally spreading TB in a wild population. Here, we synthesize more than 25 years-worth of TB reporting and social interaction data across 3,420 individuals to track disease spread, and quantify rates of TB social exposure, progression, and mortality. We found that most meerkats had been exposed to the pathogen within eight years of first detection in the study area, with exposure reaching up to 95% of the population. Approximately one quarter of exposed individuals progressed to clinical TB stages, followed by physical deterioration and death within a few months. Since emergence, 11.6% of deaths were attributed to TB, although the true toll of TB-related mortality is likely higher. Lastly, we observed marked variation in disease progression among individuals, suggesting inter-individual differences in both TB susceptibility and resistance. Our results highlight that TB prevalence and mortality could be higher than previously reported, particularly in species or populations with complex social group dynamics. Long-term studies, such as the present one, allow us to assess temporal variation in disease prevalence and progression and quantify exposure, which is rarely measured in wildlife. Long-term studies are highly valuable tools to explore disease emergence and ecology, and study host-pathogen co-evolutionary dynamics in general, and its impact on social mammals.

In the last decades fungal pathogens are causing devastating population declines across a broad range of taxa. A newly emerging fungal disease, sea turtle egg fusariosis, caused by members of the Fusarium solani species complex (FSSC), has been reported to be responsible for hatching failure in sea turtles around the world. However, this has not been reported in other non-marine turtle species. Herein we report high hatching failure from eggs symptomatic of fusariosis in the yellow-spotted Amazon river turtle ( Podocnemis unifilis), inhabiting a pristine environment in the Ecuadorian Amazon. We assessed hatching success from eggs symptomatic and asymptomatic of fusariosis ( n = 680 eggs), tested for Fusarium infection by PCR amplifying the TEF-1α gene (n= 68 turtle internal egg swab samples) and sequenced eight amplicons for screening of FSSC membership on an Illumina Miseq. Hatchability was 72% for asymptomatic eggs, whilst only 8% of symptomatic eggs hatched. Eight percent of asymptomatic and 58% of symptomatic eggs tested positive for Fusarium spp. and sequencing revealed that nine sequence variants from three asymptomatic and four symptomatic eggs corresponded to F. keratoplasticum, F. solani and F. falciforme, the three major FSSC pathogens already reported in sea turtle egg fusariosis. Our study therefore suggests that observed hatching failure of eggs showing symptoms of fusariosis is at least partially caused by Fusarium pathogens within FSSC in a freshwater turtle. This report highlights that fusariosis is more widespread among the Testudines order than previously reported and is not limited to sea environments, which is of particular conservation concern.

Daily light-dark cycles shape the physiology and activity patterns of nearly all organisms. Recent evidence that gut microbial oscillations synchronise circadian rhythms in host immunity and metabolism indicate that diurnal dynamics is a crucial component of microbiome function. However, their prevalence and functional significance are rarely tested in natural populations. Here we summarize the hallmarks of gut microbiota oscillations and the mechanisms by which they synchronise rhythms in host immunity and metabolism. We discuss the consequences for diverse biological processes such as host pathogen susceptibility and seasonal switches in metabolism, and outline how the breakdown of these circadian interactions, for example during senescence and as a consequence of urbanisation, may affect wildlife infection risk and disease. Lastly, we provide practical guidelines for the measurement of microbial oscillations in wildlife, highlighting that whilst wild animals are rarely available over a 24-hour period, characterising even parts of the cycle can be informative. Light-dark cycles are an almost universal environmental cue and provide a rare opportunity to generalise gut microbial responses across species. An improved understanding of how microbial rhythms manifest in wildlife is essential to fully comprehend their ecological significance. 

Genotyping novel complex multigene families is particularly challenging in non-model organisms. Target primers frequently amplify simultaneously multiple loci leading to high PCR and sequencing artefacts such as chimeras and allele amplification bias. Most genotyping pipelines have been validated in non-model systems whereby the real genotype is unknown and the generation of artefacts may be highly repeatable. Further hindering accurate genotyping, the relationship between artefacts and genotype complexity (i.e. number of alleles per genotype) within a PCR remains poorly described. Here we investigated the latter by experimentally combining multiple known major histocompatibility complex (MHC) haplotypes of a model organism (chicken, \textit{Gallus gallus}, 43 artificial genotypes with 2-13 alleles per amplicon). In addition to well defined “optimal” primers, we simulated a non-model species situation by designing “cross-species” primers, with sequence data from closely related Galliforme species. We applied a novel open-source genotyping pipeline (ACACIA; \url{https://gitlab.com/psc_santos/ACACIA}), and compared its performance with another, previously published pipeline (AmpliSAS). Allele calling accuracy was higher when using ACACIA (98.5\% vs 97\% and 77.8\% vs 75.2\% for the “optimal” and “cross-species” datasets respectively). Systematic allele dropout of three alleles owing to primer mismatch in the “cross-species” dataset explained high allele calling repeatability (100\% when using ACACIA) despite low accuracy, demonstrating that repeatability can be misleading when evaluating genotyping workflows. Genotype complexity was positively associated with non-chimeric artefacts, chimeric artefacts (nonlinearly by leveling when amplifying more than 4-6 alleles) and allele amplification bias. Our study exemplifies and demonstrates pitfalls researchers should avoid to reliably genotype complex multigene families.

As microbiome research moves away from model organisms to wildlife, new challenges for microbiome high throughput sequencing arise caused by the variety of wildlife diets. High levels of contamination are commonly observed emanating from the host (mitochondria) or diet (chloroplast). Such high contamination levels affect the overall sequencing depth of wildlife samples thus decreasing statistical power and leading to poor performance in downstream analysis. We developed an amplification protocol utilizing PNA-DNA clamps to maximize the use of resources and to increase the sampling depth of true microbiome sequences in samples with high levels of plastid contamination. We chose two study organisms, a bat (Leptonyteris yerbabuenae) and a bird (Mimus parvulus), both relying on heavy plant-based diets that sometimes lead to traces of plant-based faecal material producing high contamination signals from chloroplasts and mitochondria. On average, our protocol yielded a 13-fold increase in bacterial sequence amplification compared with the standard protocol (Earth Microbiome Protocol) used in wildlife research. For both focal species, we were able significantly to increase the percentage of sequences available for downstream analyses after the filtering of plastids and mitochondria. Our study presents the first results obtained by using PNA-DNA clamps to block the PCR amplification of chloroplast and mitochondrial DNA from the diet in the gut microbiome of wildlife. The method involves a cost-effective molecular technique instead of the filtering out of unwanted sequencing reads. As 33% and 26% of birds and bats, respectively, have a plant-based diet, the tool that we present here will optimize the sequencing and analysis of wild microbiomes.