Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Data from: The excreted microbiota of bats: evidence of niche specialization based on multiple body habitats

Animal-associated microbiotas form complex communities, which play crucial functions for their host, including susceptibility to infections. Despite increasing attention to bats as reservoirs of zoonotic pathogens, their microbiota is poorly documented, especially for samples potentially implicated in pathogen transmission such as urine and saliva. Here, using low-biomass individual samples, we examined the composition and structure of bacterial communities excreted by insectivorous bats, focusing on three body habitats (saliva, urine and faeces). We show that niche specialisation occurs as bacterial community composition was distinct across body habitats with the majority of phylotypes being body habitat specific. Our results suggest that urine harbours more diverse bacterial communities than saliva and faeces and reveal potentially zoonotic bacteria such as Leptospira, Rickettsia, Bartonella and Coxiella in all body habitats. Our study emphasised that, in addition to the traditional use of gut-associated samples such as faeces, both urine and saliva are also of interest because of their diverse microbiota and the potential transmission of pathogenic bacteria. Our results represent a critical baseline for future studies investigating the interactions between microbiota and infection dynamics in bats

Data from: The excreted microbiota of bats: evidence of niche specialization based on multiple body habitats

Animal-associated microbiotas form complex communities, which play crucial functions for their host, including susceptibility to infections. Despite increasing attention to bats as reservoirs of zoonotic pathogens, their microbiota is poorly documented, especially for samples potentially implicated in pathogen transmission such as urine and saliva. Here, using low-biomass individual samples, we examined the composition and structure of bacterial communities excreted by insectivorous bats, focusing on three body habitats (saliva, urine and faeces). We show that niche specialisation occurs as bacterial community composition was distinct across body habitats with the majority of phylotypes being body habitat specific. Our results suggest that urine harbours more diverse bacterial communities than saliva and faeces and reveal potentially zoonotic bacteria such as Leptospira, Rickettsia, Bartonella and Coxiella in all body habitats. Our study emphasised that, in addition to the traditional use of gut-associated samples such as faeces, both urine and saliva are also of interest because of their diverse microbiota and the potential transmission of pathogenic bacteria. Our results represent a critical baseline for future studies investigating the interactions between microbiota and infection dynamics in bats

Supplementary Material from "Synchronized shift of oral, fecal and urinary microbiotas in bats and natural infection dynamics during seasonal reproduction"

Additional texts, figures and tables showing details of bat samples, laboratory protocols and statistical analyses

Diversity of <i>Bartonella</i> and <i>Rickettsia</i> spp. in Bats and Their Blood-Feeding Ectoparasites from South Africa and Swaziland - Fig 2

<p><b>Phylogenetic relationships of Bartonella (A) and Rickettsia (B) spp. detected in bats and their ectoparasites from South Africa and Swaziland.</b> Black dots indicate bootstrap > 0.75. Bootstrap values for nodes of interest are indicated by an arrow. Trees were built under the TIM3+G and TIM1+G models of evolution, for <i>Bartonella</i> and <i>Rickettsia</i> spp. respectively. The sequences generated in this study are in red and are coded with the sample ID, the host species and geographic location abbreviation as indicated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152077#pone.0152077.g001" target="_blank">Fig 1</a>. Reference sequences (retrieved from GenBank) corresponding to bat- and rodent-associated samples are in blue and grey, respectively. Sequences associated with <i>Miniopterus</i> and <i>Rousettus</i> bats are denoted by an asterisk (*) and a triangle (▲) respectively. GenBank accession numbers are indicated in parentheses.</p

A metagenomic viral discovery approach identifies potential zoonotic and novel mammalian viruses in <i>Neoromicia</i> bats within South Africa

<div><p>Species within the <i>Neoromicia</i> bat genus are abundant and widely distributed in Africa. It is common for these insectivorous bats to roost in anthropogenic structures in urban regions. Additionally, <i>Neoromicia capensis</i> have previously been identified as potential hosts for Middle East respiratory syndrome (MERS)-related coronaviruses. This study aimed to ascertain the gastrointestinal virome of these bats, as viruses excreted in fecal material or which may be replicating in rectal or intestinal tissues have the greatest opportunities of coming into contact with other hosts. Samples were collected in five regions of South Africa over eight years. Initial virome composition was determined by viral metagenomic sequencing by pooling samples and enriching for viral particles. Libraries were sequenced on the Illumina MiSeq and NextSeq500 platforms, producing a combined 37 million reads. Bioinformatics analysis of the high throughput sequencing data detected the full genome of a novel species of the <i>Circoviridae</i> family, and also identified sequence data from the <i>Adenoviridae</i>, <i>Coronaviridae</i>, <i>Herpesviridae</i>, <i>Parvoviridae</i>, <i>Papillomaviridae</i>, <i>Phenuiviridae</i>, and <i>Picornaviridae</i> families. Metagenomic sequencing data was insufficient to determine the viral diversity of certain families due to the fragmented coverage of genomes and lack of suitable sequencing depth, as some viruses were detected from the analysis of reads-data only. Follow up conventional PCR assays targeting conserved gene regions for the <i>Adenoviridae</i>, <i>Coronaviridae</i>, and <i>Herpesviridae</i> families were used to confirm metagenomic data and generate additional sequences to determine genetic diversity. The complete coding genome of a MERS-related coronavirus was recovered with additional amplicon sequencing on the MiSeq platform. The new genome shared 97.2% overall nucleotide identity to a previous <i>Neoromicia</i>-associated MERS-related virus, also from South Africa. Conventional PCR analysis detected diverse adenovirus and herpesvirus sequences that were widespread throughout <i>Neoromicia</i> populations in South Africa. Furthermore, similar adenovirus sequences were detected within these populations throughout several years. With the exception of the coronaviruses, the study represents the first report of sequence data from several viral families within a Southern African insectivorous bat genus; highlighting the need for continued investigations in this regard.</p></div

<i>Phenuiviridae</i> sequence identified from the <i>Neoromicia</i> virome.

<p><b>A)</b> Alignment of the <i>Phenuiviridae</i> contig in reference to a typical L segment gene. <b>B)</b> The phylogenetic tree was constructed with a 267 bp region of the bunyavirus L genome segment using BEAST v1.8 with the GTR substitution model plus invariant sites. Relevant genera are shown on the right and GenBank accession numbers of each sequence are provided; the novel <i>Neoromicia</i> bunyavirus sequence from this study is indicated with a black circle. SFTSV = Severe fever with thrombocytopenia syndrome virus.</p

<i>Neoromicia</i> adenovirus sequences.

<p><b>A)</b> Overview of confirmed mastadenovirus contigs from the <i>Neoromicia</i> virome created with Velvet and CLC assemblers as they align to a characteristic mastadenovirus genome. The dark grey contig was used in B, along with the amplicons produced by conventional PCR (depicted by the checkered block). <b>B)</b> Bayesian phylogenetic tree of a 237 bp region of the DNA polymerase gene. The phylogeny was constructed in BEAST v1.8 using the Hasegawa, Kishino and Yano (HKY) substitution model plus gamma distribution model suggested by J-model test. The MCMC chain was set to 20,000,000 generations sampled every 2000 steps, with a 10% burn-in of the first generated trees. Adenovirus sequences detected from this study are shown with black circles, and bat species from which adenoviruses originated are indicated on the right side of the sequence names. Posterior probability values of less than 50% were omitted. GenBank accession numbers are shown next to sequences.</p

<i>Betacoronavirus</i> full genome phylogeny.

<p><b>A)</b> The full genome phylogeny of 4 lineages (A-D) of the genus <i>Betacoronavirus</i> constructed using BEAST software with the GTR substitution model using invariant sites and gamma distribution. The MCMC chain was set to 15,000,000 generations sampled every 1500 steps, with a 10% burn-in of the first generated trees and displayed as a radial tree in Figtree. The lineages are indicated with clipart images of host species. Also displayed are the averaged pairwise similarities between lineages as well as highlighted similarities between human coronaviruses and related viruses identified in bats (and other animals). <b>B)</b> Close-up of the external nodes of the lineage B phylogeny to show relative distances of human and civet SARS-CoV strains and SARS-related <i>Rhinolophus</i> strains (WIV1, Rp3, Rm1 and HKU3). <b>C)</b> Close-up of the lineage C external nodes depicting the human and camel MERS strains with the bat MERS-related viruses (BtCoVNeo5038 from this study is indicated with a star). Sequence abbreviations and GenBank accession numbers are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194527#pone.0194527.s011" target="_blank">S10 Table</a>.</p