Microbial Diversity and Parasitic Load in Tropical Fish of Different Environmental Conditions.

In this study we analysed fecal bacterial communities and parasites of three important Indonesian fish species, Epinephelus fuscoguttatus, Epinephelus sexfasciatus and Atule mate. We then compared the biodiversity of bacterial communities and parasites of these three fish species collected in highly polluted Jakarta Bay with those collected in less polluted Indonesian areas of Cilacap (E. sexfasciatus, A. mate) and Thousand Islands (E. fuscoguttatus). In addition, E. fuscoguttatus from net cages in an open water mariculture facility was compared with free living E. fuscoguttatus from its surroundings. Both core and shared microbiomes were investigated. Our results reveal that, while the core microbiomes of all three fish species were composed of fairly the same classes of bacteria, the proportions of these bacterial classes strongly varied. The microbial composition of phylogenetically distant fish species, i.e. A. mate and E. sexfasciatus from Jakarta Bay and Cilacap were more closely related than the microbial composition of more phylogentically closer species, i.e. E. fuscoguttatus, E. sexfasciatus from Jakarta Bay, Cilacap and Thousand Islands. In addition, we detected a weak negative correlation between the load of selected bacterial pathogens, i.e. Vibrio sp. and Photobacterium sp. and the number of endoparasites. In the case of Flavobacterium sp. the opposite was observed, i.e. a weak positive correlation. Of the three recorded pathogenic bacterial genera, Vibrio sp. was commonly found in E. fuscoguttatus from mariculture, and lessly in the vicinity of the net cages and rarely in the fishes from the heavily polluted waters from Jakarta Bay. Flavobacterium sp. showed higher counts in mariculture fish and Photobacteria sp. was the most prominent in fish inside and close to the net cages

Human local adaptation of the TRPM8 cold receptor along a latitudinal cline

Ambient temperature is a critical environmental factor for all living organisms. It was likely an important selective force as modern humans recently colonized temperate and cold Eurasian environments. Nevertheless, as of yet we have limited evidence of local adaptation to ambient temperature in populations from those environments. To shed light on this question, we exploit the fact that humans are a cosmopolitan species that inhabit territories under a wide range of temperatures. Focusing on cold perception–which is central to thermoregulation and survival in cold environments–we show evidence of recent local adaptation on TRPM8. This gene encodes for a cation channel that is, to date, the only temperature receptor known to mediate an endogenous response to moderate cold. The upstream variant rs10166942 shows extreme population differentiation, with frequencies that range from 5% in Nigeria to 88% in Finland (placing this SNP in the 0.02% tail of the FST empirical distribution). When all populations are jointly analyzed, allele frequencies correlate with latitude and temperature beyond what can be explained by shared ancestry and population substructure. Using a Bayesian approach, we infer that the allele originated and evolved neutrally in Africa, while positive selection raised its frequency to different degrees in Eurasian populations, resulting in allele frequencies that follow a latitudinal cline. We infer strong positive selection, in agreement with ancient DNA showing high frequency of the allele in Europe 3,000 to 8,000 years ago. rs10166942 is important phenotypically because its ancestral allele is protective of migraine. This debilitating disorder varies in prevalence across human populations, with highest prevalence in individuals of European descent–precisely the population with the highest frequency of rs10166942 derived allele. We thus hypothesize that local adaptation on previously neutral standing variation may have contributed to the genetic differences that exist in the prevalence of migraine among human populations today

Fish morphometrical data.

<p>Fish morphometrical data.</p

Core microbiome for each host species and shared microbiome on class level.

<p>The core microbiome is constructed by counting OTUs that are present in every sample of each host species. The shared microbiome results as a combination of all three core microbiomes, representing all OTUs in all samples of the three host fish species.</p

Parasitic load.

<p>Parasitic load.</p

Spearman’s rank-order correlation was performed to determine a relationship between the numbers of parasites against the abundance of three known fish pathogenic bacteria.

<p>It showed for <i>Vibrio</i> sp. (<i>ρ</i> = −0.4592765, <i>p</i> = 0.04164) and <i>Photobacterium</i> sp. (<i>ρ</i> − 0.04429808, <i>p</i> = 0.05045) a medium negative correlation and a weak positive correlation for <i>Flavobacterium</i> sp. (<i>ρ</i> = 0.1329735, <i>p</i> = 0.5762).</p

Experimental overview.

<p>Experimental overview.</p

Alpha diversity and beta diversity estimates across fish species, sampling location and visualization of differences in bacterial gut community composition by host species.

<p><b>a</b>: observed OTU richness; <b>b</b>: Chao1 index that estimates the true species richness of a sample; <b>c</b>: Shannon-Wiener diversity index accounting for species abundance and eveness of distribution. Dots represent estimates for individual samples, solid lines constitute the median, boxes the quartiles, and bars the interquartile range. <b>d</b>: Beta diversity is estimated with Nonmetric multidimensional scaling (NMDS) of bacterial communities derived from 20 fish specimen coloured by host species. Point shapes indicates differences in the sampling location. Samples derived from mariculture are labelled accordingly. Ordinations are based on between-sample dissimilarities calculated by Bray-Curtis distances.</p

Taxonomic summary of predominant (a) and rare (b) phyla across the three fish species.

<p>To determine the predominant phyla only OTUs with an abundance of over 0.01% per sample were selected, resulting in three phyla for <i>A. mate</i> and <i>E. sexfasciatus</i> and eight phyla for <i>E. fuscoguttatus</i>. To determine rare phyla with relative abundance counts of less than 0.01% are included in this plot. ef1-ef10 refers to all samples from <i>E. fuscoguttatus</i>, while am1-am4 belongs to <i>A. mate</i> and es1-es6 to <i>E. sexfasciatus</i>.</p