TACO: Taxonomic prediction of unknown OTUs through OTU co-abundance networks

Background: A main goal of metagenomics is taxonomic characterization of microbial communities. Although sequence comparison has been the main method for the taxonomic classification, there is not a clear agreement on similarity calculation and similarity thresholds, especially at higher taxonomic levels such as phylum and class. Thus taxonomic classification of novel metagenomic sequences without close homologs in the biological databases poses a challenge. Methods: In this study, we propose to use the co-abundant associations between taxa/operational taxonomic units (OTU) across complex and diverse communities to assist taxonomic classification. We developed a Markov Random Field model to predict taxa of unknown microorganisms using co-abundant associations. Results: Although such associations are intrinsically functional associations, we demonstrate that they are strongly correlated with taxonomic associations and can be combined with sequence comparison methods to predict taxonomic origins of unknown microorganisms at phylum and class levels. Conclusions: With the ever-increasing accumulation of sequence data from microbial communities, we now take the first step to explore these associations for taxonomic identification beyond sequence similarity. Availability and Implementation: Source codes of TACO are freely available at the following URL: https://github.com/baharvand/OTU-Taxonomy-Identification implemented in C++, supported on Linux and MS Windows.     

Assembly rules of reef corals are flexible along a steep climatic gradient

Coral reefs, one of the world's most complex and vulnerable ecosystems, face an uncertain future in coming decades as they continue to respond to anthropogenic climate change, overfishing, pollution, and other human impacts [1, 2]. Traditionally, marine macroecology is based on presence/absence data from taxonomic checklists or geographic ranges, providing a qualitative overview of spatial shifts in species richness that treats rare and common species equally [3, 4]. As a consequence, regional and long-term shifts in relative abundances of individual taxa are poorly understood. Here we apply a more rigorous quantitative approach to examine large-scale spatial variation in the species composition and abundance of corals on midshelf reefs along the length of Australia's Great Barrier Reef, a biogeographic region where species richness is high and relatively homogeneous [5]. We demonstrate that important functional components of coral assemblages "sample" space differently at 132 sites separated by up to 1740 km, leading to complex latitudinal shifts in patterns of absolute and relative abundance. The flexibility in community composition that we document along latitudinal environmental gradients indicates that climate change is likely to result in a reassortment of coral reef taxa rather than wholesale loss of entire reef ecosystems.     

Diet Alters Both the Structure and Taxonomy of the Ovine Gut Microbial Ecosystem

We surveyed the ruminal metagenomes of 16 sheep under two different diets using Illumina pair-end DNA sequencing of raw microbial DNA extracted from rumen samples. The resulting sequence data were bioinformatically mapped to known prokaryotic 16S rDNA sequences to identify the taxa present in the samples and then analysed for the presence of potentially new taxa. Strikingly, the majority of the microbial individuals found did not map to known taxa from 16S sequence databases. We used a novel statistical modelling approach to compare the taxonomic distributions between animals fed a forage-based diet and those fed concentrated grains. With this model, we found significant differences between the two groups both in the dominant taxa present in the rumen and in the overall shape of the taxa abundance curves. In general, forage-fed animals have a more diverse microbial ecosystem, whereas the concentrate-fed animals have ruminal systems more heavily dominated by a few taxa. As expected, organisms from methanogenic groups are more prevalent in forage-fed animals. Finally, all of these differences appear to be grounded in an underlying common input of new microbial individuals into the rumen environment, with common organisms from one feed group being present in the other, but at much lower abundance.     

The use of indicator taxa as representatives of communities in bioassessment

1. Sampling and processing of benthic macroinvertebrate samples is time consuming and expensive. Although a number of cost‐cutting options exist, a frequently asked question is how representative a subset of data is of the whole community, in particular in areas where habitat diversity is high (like Dutch surface water habitats). 2. Weighted averaging was used to reassign 650 samples to a typology of 40 community types, testing the representativeness of different subsets of data: (i) four different types of data (presence/absence, raw, ²log‐ and ln‐transformed abundance), (ii) three subsets of ‘indicator’ taxa (taxa with indicator weights 4–12, 7–12, and 10–12) and (iii) single taxonomic groups (n = 14) by determining the classification error. 3. ²log‐ and ln‐transformed abundances resulted in the lowest classification error, whilst the use of qualitative data resulted in a reduction of 10% of the samples assigned to their original community type compared to the use of ln‐transformed abundance data. 4. Samples from community types with a high number of unique indicator taxa had the lowest classification error, and classification error increased as similarity among community types increased. Using a subset of indicator taxa resulted in a maximum increase of the classification error of 15% when only taxa with an indicator weight 10–12 were included (error = 49.1%). 5. Use of single taxonomic groups resulted in high classification error, the lowest classification error was found using Trichoptera (68%), and was related to the frequency of the taxonomic group among samples and the indicator weights of the taxa. 6. Our findings that the use of qualitative data, subsets of indicator taxa or single taxonomic groups resulted in high classification error implies low taxonomic redundancy, and supports the use of all taxa in characterising a macroinvertebrate community, in particular in areas where habitat diversity is high.     

Winter Planktonic Microbial Communities in Highland Aquatic Habitats

Winter conditions in aquatic habitats of the temperate zone markedly differ from those present in warmer seasons, nevertheless, relatively scarce information is available on planktonic microbial composition, as sites are not easily accessible and it was supposed traditionally that microbial activity is low during this cold period. Since microorganisms could have great impact on the ecosystem even during winter, we explored various sites in the Eastern Carpathians regarding the abundance and taxonomic composition of planktonic microorganisms. Although many of the studied environments were extreme habitats, planktonic microbial communities were abundant and mostly diverse with the presence of previously unidentified taxa.     

Mock microbial community meta-analysis using different trimming of amplicon read lengths

Trimming of sequencing reads is a pre-processing step that aims to discard sequence segments such as primers, adapters and low quality nucleotides that will interfere with clustering and classification steps. We evaluated the impact of trimming length of paired-end 16S and 18S rRNA amplicon reads on the ability to reconstruct the taxonomic composition and relative abundances of communities with a known composition in both even and uneven proportions. We found that maximizing read retention maximizes recall but reduces precision by increasing false positives. The presence of expected taxa was accurately predicted across broad trim length ranges but recovering original relative proportions remains a difficult challenge. We show that parameters that maximize taxonomic recovery do not simultaneously maximize relative abundance accuracy. Trim length represents one of several experimental parameters that have non-uniform impact across microbial clades, making it a difficult parameter to optimize. This study offers insights, guidelines, and helps researchers assess the significance of their decisions when trimming raw reads in a microbiome analysis based on overlapping or non-overlapping paired-end amplicons.     

Identifying the microbial taxa that consistently respond to soil warming across time and space

Soil microbial communities are the key drivers of many terrestrial biogeochemical processes. However, we currently lack a generalizable understanding of how these soil communities will change in response to predicted increases in global temperatures and which microbial lineages will be most impacted. Here, using high‐throughput marker gene sequencing of soils collected from 18 sites throughout North America included in a 100‐day laboratory incubation experiment, we identified a core group of abundant and nearly ubiquitous soil microbes that shift in relative abundance with elevated soil temperatures. We then validated and narrowed our list of temperature‐sensitive microbes by comparing the results from this laboratory experiment with data compiled from 210 soils representing multiple, independent global field studies sampled across spatial gradients with a wide range in mean annual temperatures. Our results reveal predictable and consistent responses to temperature for a core group of 189 ubiquitous soil bacterial and archaeal taxa, with these taxa exhibiting similar temperature responses across a broad range of soil types. These microbial ‘bioindicators’ are useful for understanding how soil microbial communities respond to warming and to discriminate between the direct and indirect effects of soil warming on microbial communities. Those taxa that were found to be sensitive to temperature represented a wide range of lineages and the direction of the temperature responses were not predictable from phylogeny alone, indicating that temperature responses are difficult to predict from simply describing soil microbial communities at broad taxonomic or phylogenetic levels of resolution. Together, these results lay the foundation for a more predictive understanding of how soil microbial communities respond to soil warming and how warming may ultimately lead to changes in soil biogeochemical processes.     

The Western English Channel contains a persistent microbial seed bank

Robust seasonal dynamics in microbial community composition have previously been observed in the English Channel L4 marine observatory. These could be explained either by seasonal changes in the taxa present at the L4 site, or by the continuous modulation of abundance of taxa within a persistent microbial community. To test these competing hypotheses, deep sequencing of 16S rRNA from one randomly selected time point to a depth of 10 729 927 reads was compared with an existing taxonomic survey data covering 6 years. When compared against the 6-year survey of 72 shallow sequenced time points, the deep sequenced time point maintained 95.4% of the combined shallow OTUs. Additionally, on average, 99.75%±0.06 (mean±s.d.) of the operational taxonomic units found in each shallow sequenced sample were also found in the single deep sequenced sample. This suggests that the vast majority of taxa identified in this ecosystem are always present, but just in different proportions that are predictable. Thus observed changes in community composition are actually variations in the relative abundance of taxa, not, as was previously believed, demonstrating extinction and recolonization of taxa in the ecosystem through time.     

Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance

The abundance of different SSU rRNA (“16S”) gene sequences in environmental samples is widely used in studies of microbial ecology as a measure of microbial community structure and diversity. However, the genomic copy number of the 16S gene varies greatly – from one in many species to up to 15 in some bacteria and to hundreds in some microbial eukaryotes. As a result of this variation the relative abundance of 16S genes in environmental samples can be attributed both to variation in the relative abundance of different organisms, and to variation in genomic 16S copy number among those organisms. Despite this fact, many studies assume that the abundance of 16S gene sequences is a surrogate measure of the relative abundance of the organisms containing those sequences. Here we present a method that uses data on sequences and genomic copy number of 16S genes along with phylogenetic placement and ancestral state estimation to estimate organismal abundances from environmental DNA sequence data. We use theory and simulations to demonstrate that 16S genomic copy number can be accurately estimated from the short reads typically obtained from high-throughput environmental sequencing of the 16S gene, and that organismal abundances in microbial communities are more strongly correlated with estimated abundances obtained from our method than with gene abundances. We re-analyze several published empirical data sets and demonstrate that the use of gene abundance versus estimated organismal abundance can lead to different inferences about community diversity and structure and the identity of the dominant taxa in microbial communities. Our approach will allow microbial ecologists to make more accurate inferences about microbial diversity and abundance based on 16S sequence data.     

Quantifying long‐term recurrence in planktonic microbial eukaryotes

How much temporal recurrence is present in microbial assemblages is still an unanswered ecological question. Even though marked seasonal changes have been reported for whole microbial communities, less is known on the dynamics and seasonality of individual taxa. Here, we aim at understanding microbial recurrence at three different levels: community, taxonomic group and operational taxonomic units (OTUs). For that, we focused on a model microbial eukaryotic community populating a long‐term marine microbial observatory using 18S rRNA gene data from two organismal size fractions: the picoplankton (0.2–3 µm) and the nanoplankton (3–20 µm). We have developed an index to quantify recurrence in particular taxa. We found that community structure oscillated systematically between two main configurations corresponding to winter and summer over the 10 years studied. A few taxonomic groups such as Mamiellophyceae or MALV‐III presented clear recurrence (i.e., seasonality), whereas 13%–19% of the OTUs in both size fractions, accounting for ~40% of the relative abundance, featured recurrent dynamics. Altogether, our work links long‐term whole community dynamics with that of individual OTUs and taxonomic groups, indicating that recurrent and non‐recurrent changes characterize the dynamics of microbial assemblages.     

Taxonomic Resolution and Quantification of Freshwater Macroinvertebrate Samples from an Australian Dryland River: The Benefits and Costs of Using Species Abundance Data

In studies using macroinvertebrates as indicators for monitoring rivers and streams, species level identifications in comparison with lower resolution identifications can have greater information content and result in more reliable site classifications and better capacity to discriminate between sites, yet many such programmes identify specimens to the resolution of family rather than species. This is often because it is cheaper to obtain family level data than species level data. Choice of appropriate taxonomic resolution is a compromise between the cost of obtaining data at high taxonomic resolutions and the loss of information at lower resolutions. Optimum taxonomic resolution should be determined by the information required to address programme objectives. Costs saved in identifying macroinvertebrates to family level may not be justified if family level data can not give the answers required and expending the extra cost to obtain species level data may not be warranted if cheaper family level data retains sufficient information to meet objectives. We investigated the influence of taxonomic resolution and sample quantification (abundance vs. presence/absence) on the representation of aquatic macroinvertebrate species assemblage patterns and species richness estimates. The study was conducted in a physically harsh dryland river system (Condamine-Balonne River system, located in south-western Queensland, Australia), characterised by low macroinvertebrate diversity. Our 29 study sites covered a wide geographic range and a diversity of lotic conditions and this was reflected by differences between sites in macroinvertebrate assemblage composition and richness. The usefulness of expending the extra cost necessary to identify macroinvertebrates to species was quantified via the benefits this higher resolution data offered in its capacity to discriminate between sites and give accurate estimates of site species richness. We found that very little information (<6%) was lost by identifying taxa to family (or genus), as opposed to species, and that quantifying the abundance of taxa provided greater resolution for pattern interpretation than simply noting their presence/absence. Species richness was very well represented by genus, family and order richness, so that each of these could be used as surrogates of species richness if, for example, surveying to identify diversity hot-spots. It is suggested that sharing of common ecological responses among species within higher taxonomic units is the most plausible mechanism for the results. Based on a cost/benefit analysis, family level abundance data is recommended as the best resolution for resolving patterns in macroinvertebrate assemblages in this system. The relevance of these findings are discussed in the context of other low diversity, harsh, dryland river systems.     

Trait-dependent declines of species following conversion of rain forest to oil palm plantations

Conversion of natural habitats to agriculture reduces species richness, particularly in highly diverse tropical regions, but its effects on species composition are less well-studied. The conversion of rain forest to oil palm is of particular conservation concern globally, and we examined how it affects the abundance of birds, beetles, and ants according to their local population size, body size, geographical range size, and feeding guild or trophic position. We re-analysed data from six published studies representing 487 species/genera to assess the relative importance of these traits in explaining changes in abundance following forest conversion. We found consistent patterns across all three taxa, with large-bodied, abundant forest species from higher trophic levels, declining most in abundance following conversion of forest to oil palm. Best-fitting models explained 39–66 % of the variation in abundance changes for the three taxa, and included all ecological traits that we considered. Across the three taxa, those few species found in oil palm tended to be small-bodied species, from lower trophic levels, that had low local abundances in forest. These species were often hyper-abundant in oil palm plantations. These results provide empirical evidence of consistent responses to land-use change among taxonomic groups in relation to ecological traits.     

高原鼠兔肠道微生物中丰富及稀有类群的季节性特征

气候及食物是驱动植食性小哺乳动物肠道菌群产生季节性变化的重要因素。然而,此类研究很少涉及肠道丰富及稀有微生物类群。本文以高原鼠兔（Ochotona curzoniae）为对象,通过16S rRNA基因测序和分析,探讨丰富及稀有肠道微生物类群的结构组成、多样性指数及功能在春、夏、秋、冬四季的变化特征。结果显示,丰富类群对菌群主要门和功能的季节性变异贡献大于稀有类群,稀有类群对菌群OTU和alpha多样性的变异贡献大于丰富类群。丰富类群和稀有类群的香农指数均在冬季显著高于其他季节;丰富类群的ACE指数在秋季显著低于其他季节,而稀有类群的ACE指数则在冬季显著高于春季和夏季。丰富类群中拟杆菌门（Bacteroidetes）的相对丰度在冬季和秋季显著高于春季和夏季,但在稀有类群中,夏季和秋季的相对丰度显著高于冬季和春季。丰富类群中氨基酸代谢通路的相对丰度在冬季显著高于春季和夏季,而在稀有类群中,其相对丰度在春季显著高于夏季和秋季。气温、降水量和植被中的营养物质与肠道菌群中丰富类群和稀有类群的变化均显著相关,环境变量对丰富类群和稀有类群变化的总解释率分别为18%（气温：3%;降水：4%;植被营养成分：10%;联合：1%）和9%（气温：1%;降水：2%;植被营养成分：5%;联合：1%）。以上结果表明肠道微生物中的丰富和稀有类群具有不同的分布模式和季节性特征,二者对整体菌群变异的贡献存在差异,环境因素更多地影响丰富类群,反映了肠道微生物不同类群对季节变化响应的非一致性。本研究增进了我们对哺乳动物肠道菌群季节性变化过程及环境适应性的认识。     

Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities

The assessment of microbial diversity and distribution is a major concern in environmental microbiology. There are two general approaches for measuring community diversity: quantitative measures, which use the abundance of each taxon, and qualitative measures, which use only the presence/absence of data. Quantitative measures are ideally suited to revealing community differences that are due to changes in relative taxon abundance (e.g., when a particular set of taxa flourish because a limiting nutrient source becomes abundant). Qualitative measures are most informative when communities differ primarily by what can live in them (e.g., at high temperatures), in part because abundance information can obscure significant patterns of variation in which taxa are present. We illustrate these principles using two 16S rRNA-based surveys of microbial populations and two phylogenetic measures of community beta diversity: unweighted UniFrac, a qualitative measure, and weighted UniFrac, a new quantitative measure, which we have added to the UniFrac website (http://bmf.colorado.edu/unifrac). These studies considered the relative influences of mineral chemistry, temperature, and geography on microbial community composition in acidic thermal springs in Yellowstone National Park and the influences of obesity and kinship on microbial community composition in the mouse gut. We show that applying qualitative and quantitative measures to the same data set can lead to dramatically different conclusions about the main factors that structure microbial diversity and can provide insight into the nature of community differences. We also demonstrate that both weighted and unweighted UniFrac measurements are robust to the methods used to build the underlying phylogeny.     

VITCOMIC2: visualization tool for the phylogenetic composition of microbial communities based on 16S rRNA gene amplicons and metagenomic shotgun sequencing

Background

The 16S rRNA gene-based amplicon sequencing analysis is widely used to determine the taxonomic composition of microbial communities. Once the taxonomic composition of each community is obtained, evolutionary relationships among taxa are inferred by a phylogenetic tree. Thus, the combined representation of taxonomic composition and phylogenetic relationships among taxa is a powerful method for understanding microbial community structure; however, applying phylogenetic tree-based representation with information on the abundance of thousands or more taxa in each community is a difficult task. For this purpose, we previously developed the tool VITCOMIC (VIsualization tool for Taxonomic COmpositions of MIcrobial Community), which is based on the genome-sequenced microbes’ phylogenetic information. Here, we introduce VITCOMIC2, which incorporates substantive improvements over VITCOMIC that were necessary to address several issues associated with 16S rRNA gene-based analysis of microbial communities.

Results

We developed VITCOMIC2 to provide (i) sequence identity searches against broad reference taxa including uncultured taxa; (ii) normalization of 16S rRNA gene copy number differences among taxa; (iii) rapid sequence identity searches by applying the graphics processing unit-based sequence identity search tool CLAST; (iv) accurate taxonomic composition inference and nearly full-length 16S rRNA gene sequence reconstructions for metagenomic shotgun sequencing; and (v) an interactive user interface for simultaneous representation of the taxonomic composition of microbial communities and phylogenetic relationships among taxa. We validated the accuracy of processes (ii) and (iv) by using metagenomic shotgun sequencing data from a mock microbial community.

Conclusions

The improvements incorporated into VITCOMIC2 enable users to acquire an intuitive understanding of microbial community composition based on the 16S rRNA gene sequence data obtained from both metagenomic shotgun and amplicon sequencing.

     

Regional‐scale patterns and predictors of species richness and abundance across twelve major tropical inter‐reef taxa

Species richness and abundance are biodiversity metrics widely used to describe and estimate changes in biodiversity. Studies of marine species richness and abundance typically focus on one, or just a few, taxa. Consequently, it is currently not possible to understand the performance of predictors of species richness and abundance across marine taxa. Using a taxonomically comprehensive dataset of twelve major taxa of flora and fauna from eight phyla sampled from the inter‐reef seabed region of the Great Barrier Reef, Australia, we used boosted regression trees to test the performance of fourteen environmental and spatial predictors of species richness and abundance. Sediment composition predicted richness best for all taxa: gravel contributed up to 39% relative influence for one group and all taxa had low richness in muddy habitats. Sea surface temperature, seabed current shear stress, depth and latitude were also influential predictors for species richness for eight groups. Sediment was frequently an influential predictor for abundance also, while distance to domain (reef/coast) and longitude were relatively influential for six taxa. Within‐site richness was correlated between nearly all pairs of taxa, as was within‐site abundance, however ρ values were low. Overall, model performance was high, explaining up to 62% deviance of species richness, and 38% of abundance. Typically, deviance explained was greater for richness than abundance and may indicate that some drivers of species richness operate independently of any effects on species richness mediated by their effect on abundance. Deviance explained differed most between richness and abundance for bryozoans (23.3% difference) and soft corals (15.2% difference). While sediments were consistently the best predictors across all taxa, the inconsistent influence of all other predictors across taxonomic groups, as well as the low correlation of richness and abundance across taxonomic groups, cautions against predicting regional patterns of species richness and abundance from few taxa.     

The effect of excluding diatom taxa and reducing taxonomic resolution on multivariate analyses and stream bioassessment

The goal of the present study was to evaluate whether the Eastern Canadian Diatom Index (IDEC: Indice Diatomées de l’Est du Canada), which was built on fine-scale taxonomic resolution and included all observed diatom taxa, would perform similarly if a number of taxa were excluded from the analyses or if a reduced level of taxonomic resolution was used. The effects of excluding taxa and reducing the taxonomic resolution were evaluated by studying community structure variations in ordination analyses, and more specifically by comparing IDEC values calculated from the original diatom matrix with IDEC values obtained from simplified diatom matrices. The results showed that the exclusion of taxa based on the relative abundance criterion is the most appropriate, while the exclusion of taxa based on the frequency of occurrence criterion greatly affected the structure of the ordination. More specifically, taxa with a maximum relative abundance <2% can be excluded from the CA without markedly affecting the results. As a result, 125 taxa (40%) were excluded from the 311 taxa included in the original matrix without significantly affecting the performance of the IDEC. Excluding a greater number of taxa still allows for the distinction between impacted and reference sites, although subtle changes in the ecological status are lost. Ordinations based on presence/absence or genus-level identification resulted in a loss of information on subtle changes, but gross separation between impacted and reference sites was still possible.     

Minority species influences microbiota formation: the role of Bifidobacterium with extracellular glycosidases in bifidus flora formation in breastfed infant guts

The human body houses a variety of microbial ecosystems, such as the microbiotas on the skin, in the oral cavity and in the digestive tract. The gut microbiota is one such ecosystem that contains trillions of bacteria, and it is well established that it can significantly influence host health and diseases. With the advancement in bioinformatics tools, numerous comparative studies based on 16S ribosomal RNA (rRNA) gene sequences, metabolomics, pathological and epidemical analyses have revealed the correlative relationship between the abundance of certain taxa and disease states or amount of certain causative bioactive compounds. However, the 16S rRNA-based taxonomic analyses using next-generation sequencing (NGS) technology essentially detect only the majority species. Although the entire gut microbiome consists of 10¹³ microbial cells, NGS read counts are given in multiples of 10⁶, making it difficult to determine the diversity of the entire microbiota. Some recent studies have reported instances where certain minority species play a critical role in creating locally stable conditions for other species by stabilizing the fundamental microbiota, despite their low abundance. These minority species act as ‘keystone species’, which is a species whose effect on the community is disproportionately large compared to its relative abundance. One of the attributes of keystone species within the gut microbiota is its extensive enzymatic capacity for substrates that are rare or difficult to degrade for other species, such as dietary fibres or host-derived complex glycans, like human milk oligosaccharides (HMOs). In this paper, we propose that more emphasis should be placed on minority taxa and their possible role as keystone species in gut microbiota studies by referring to our recent studies on HMO-mediated microbiota formation in the infant gut.     

Resolution of the species problem in African trypanosomes

There is a general assumption that eukaryote species are demarcated by morphological or genetic discontinuities. This stems from the idea that species are defined by the ability of individuals to mate and produce viable progeny. At the microscopic level, where organisms often proliferate more by asexual than sexual reproduction, this tidy classification system breaks down and species definition becomes messy and problematic. The dearth of morphological characters to distinguish microbial species has led to the widespread application of molecular methods for identification. As well as providing molecular markers for species identification, gene sequencing has generated the data for accurate estimation of relatedness between different populations of microbes. This has led to recognition of conflicts between current taxonomic designations and phylogenetic placement. In the case of microbial pathogens, the extent to which taxonomy has been driven by utilitarian rather than biological considerations has been made explicit by molecular phylogenetic analysis. These issues are discussed with reference to the taxonomy of the African trypanosomes, where pathogenicity, host range and distribution have been influential in the designation of species and subspecies. Effectively, the taxonomic units recognised are those that are meaningful in terms of human or animal disease. The underlying genetic differences separating the currently recognised trypanosome taxa are not consistent, ranging from genome-wide divergence to presence/absence of a single gene. Nevertheless, if even a minor genetic difference reflects adaptation to a particular parasitic niche, for example, in Trypanosoma brucei rhodesiense, the presence of a single gene conferring the ability to infect humans, then it can prove useful as an identification tag for the taxon occupying that niche. Thus, the species problem can be resolved by bringing together considerations of utility, genetic difference and adaptation.