CAIM: coverage-based analysis for identification of microbiome.

Accurate taxonomic profiling of microbial taxa in a metagenomic sample is vital to gain insights into microbial ecology. Recent advancements in sequencing technologies have contributed tremendously toward understanding these microbes at species resolution through a whole shotgun metagenomic approach. In this study, we developed a new bioinformatics tool, coverage-based analysis for identification of microbiome (CAIM), for accurate taxonomic classification and quantification within both long- and short-read metagenomic samples using an alignment-based method. CAIM depends on two different containment techniques to identify species in metagenomic samples using their genome coverage information to filter out false positives rather than the traditional approach of relative abundance. In addition, we propose a nucleotide-count-based abundance estimation, which yield lesser root mean square error than the traditional read-count approach. We evaluated the performance of CAIM on 28 metagenomic mock communities and 2 synthetic datasets by comparing it with other top-performing tools. CAIM maintained a consistently good performance across datasets in identifying microbial taxa and in estimating relative abundances than other tools. CAIM was then applied to a real dataset sequenced on both Nanopore (with and without amplification) and Illumina sequencing platforms and found high similarity of taxonomic profiles between the sequencing platforms. Lastly, CAIM was applied to fecal shotgun metagenomic datasets of 232 colorectal cancer patients and 229 controls obtained from 4 different countries and 44 primary liver cancer patients and 76 controls. The predictive performance of models using the genome-coverage cutoff was better than those using the relative-abundance cutoffs in discriminating colorectal cancer and primary liver cancer patients from healthy controls with a highly confident species markers.

Inter- and intra-observer variation in phytolith morphometry.

BACKGROUND: Archaeobotanists and palaeoecologists extensively use geometric morphometrics to identify plant opal phytoliths. Particularly when applied to assemblages of phytoliths from concentrations retrieved from closed contexts, morphometric data from archaeological phytoliths compared with similar data from reference material may allow taxonomic attribution. Observer variation is one aspect of phytolith morphometry that has received little attention but may be an important source of error, and hence cause of potential misidentification of plant remains. SCOPE: To investigate inter- and intra-observer variation in phytolith morphometry, eight researchers (observers) from different laboratories measured 50 samples each from three phytolith morphotypes, Bilobate, Bulliform flabellate and Elongate dendritic, three times, under the auspices of the International Committee for Phytolith Morphometrics (ICPM). METHODS: Data for 17 size and shape variables were collected for each phytolith by manually digitising a phytolith outline (mask) from a photograph, followed by measurement of the mask with open-source morphometric software. KEY RESULTS: Inter-observer variation ranged from 0 to 23% difference from the mean of all observers. Intra-observer variation ranged from 0 to 9% difference from the mean of individual observers per week. Inter- and intra-observer variation was generally higher among inexperienced researchers. CONCLUSIONS: Scaling errors were a major cause of variation and occurred more with less experienced researchers, which is likely related to familiarity with data collection. The results indicate that inter- and intra-observer variation can be substantially reduced by providing clear instructions for and training with the equipment, photo capturing, software, data collection and data cleaning. In this paper, the ICPM provides recommendations to minimise variation.Advances in automatic data collection may eventually reduce inter- and intra-observer variation, but until this is common practice, the ICPM recommends that phytolith morphometric analyses adhere to standardised guidelines to assure that measured phytolith variables are accurate, consistent and comparable between different researchers and laboratories.

Genome-based taxonomic identification and safety assessment of an Enterococcus strain isolated from a homemade dairy product.

The aim of this study was to explore the taxonomic identification and evaluate the safety of a bacterium, Enterococcus lactis IDCC 2105, isolated from homemade cheese in Korea, using whole genome sequence (WGS) analysis. It sought to identify the species level of this Enterococcus spp., assess its antibiotic resistance, and evaluate its virulence potential. WGS analysis confirmed the bacterial strain IDCC 2105 as E. lactis and identified genes responsible for resistance to erythromycin and clindamycin, specifically msrC, and eatAv, which are chromosomally located, indicating a minimal risk for horizontal gene transfer. The absence of plasmids in E. lactis IDCC 2105 further diminishes the likelihood of resistance gene dissemination. Additionally, our investigation into seven virulence factors, including hemolysis, platelet aggregation, biofilm formation, hyaluronidase, gelatinase, ammonia production, and ß-glucuronidase activity, revealed no detectable virulence traits. Although bioinformatic analysis suggested the presence of collagen adhesion genes acm and scm, these were not corroborated by phenotypic virulence assays. Based on these findings, E. lactis IDCC 2105 presents as a safe strain for potential applications, contributing valuable information on its taxonomy, antibiotic resistance profile, and lack of virulence factors, supporting its use in food products.

New assessment of Anopheles vector species identification using MALDI-TOF MS.

BACKGROUND: Anopheles species identification is essential for an effective malaria vector control programme. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) has been developed to identify adult Anopheles species, using the legs or the cephalothorax. The protein repertoire from arthropods can vary according to compartment, but there is no general consensus regarding the anatomic part to be used. METHODS: To determine the body part of the Anopheles mosquitoes best suited for the identification of field specimens, a mass spectral library was generated with head, thorax with wings and legs of Anopheles gambiae, Anopheles arabiensis and Anopheles funestus obtained from reference centres. The MSL was evaluated using two independent panels of 52 and 40 An. gambiae field-collected in Mali and Guinea, respectively. Geographic variability was also tested using the panel from Mali and several databases containing added specimens from Mali and Senegal. RESULTS: Using the head and a database without specimens from the same field collection, the proportion of interpretable and correct identifications was significantly higher than using the other body parts at a threshold value of 1.7 (p < 0.0001). The thorax of engorged specimens was negatively impacted by the blood meal after frozen storage. The addition of specimens from Mali into the database significantly improved the results of Mali panel (p < 0.0001), which became comparable between head and legs. With higher identification scores, the using of the head will allow to decrease the number of technical replicates of protein extract per specimen, which represents a significant improvement for routine use of MALDI-TOF MS. CONCLUSIONS: The using of the head of Anopheles may improve the performance of MALDI-TOF MS. Region-specific mass spectrum databases will have to be produced. Further research is needed to improve the standardization in order to share online spectral databases.

Taxonomic identification bias does not drive patterns of abundance and diversity in theropod dinosaurs.

The ability of palaeontologists to correctly diagnose and classify new fossil species from incomplete morphological data is fundamental to our understanding of evolution. Different parts of the vertebrate skeleton have different likelihoods of fossil preservation and varying amounts of taxonomic information, which could bias our interpretations of fossil material. Substantial previous research has focused on the diversity and macroevolution of non-avian theropod dinosaurs. Theropods provide a rich dataset for analysis of the interactions between taxonomic diagnosability and fossil preservation. We use specimen data and formal taxonomic diagnoses to create a new metric, the Likelihood of Diagnosis, which quantifies the diagnostic likelihood of fossil species in relation to bone preservation potential. We use this to assess whether a taxonomic identification bias impacts the non-avian theropod fossil record. We find that the patterns of differential species abundance and clade diversity are not a consequence of their relative diagnosability. Although there are other factors that bias the theropod fossil record that are not investigated here, our results suggest that patterns of relative abundance and diversity for theropods might be more representative of Mesozoic ecology than often considered.

Application of matrix-assisted laser desorption/ionization mass spectrometry to identify species of Neotropical Anopheles vectors of malaria.

BACKGROUND: Malaria control in Panama is problematic due to the high diversity of morphologically similar Anopheles mosquito species, which makes identification of vectors of human Plasmodium challenging. Strategies by Panamanian health authorities to bring malaria under control targeting Anopheles vectors could be ineffective if they tackle a misidentified species. METHODS: A rapid mass spectrometry identification procedure was developed to accurately and timely sort out field-collected Neotropical Anopheles mosquitoes into vector and non-vector species. Matrix-assisted laser desorption/ionization (MALDI) mass spectra of highly-abundant proteins were generated from laboratory-reared mosquitoes using different extraction protocols, body parts, and sexes to minimize the amount of material from specimen vouchers needed and optimize the protocol for taxonomic identification. Subsequently, the mass spectra of field-collected Neotropical Anopheles mosquito species were classified using a combination of custom-made unsupervised (i.e., Principal component analysis-PCA) and supervised (i.e., Linear discriminant analysis-LDA) classification algorithms. RESULTS: Regardless of the protocol used or the mosquito species and sex, the legs contained the least intra-specific variability with enough well-preserved proteins to differentiate among distinct biological species, consistent with previous literature. After minimizing the amount of material needed from the voucher, one leg was enough to produce reliable spectra between specimens. Further, both PCA and LDA were able to classify up to 12 mosquito species, from different subgenera and seven geographically spread localities across Panama using mass spectra from one leg pair. LDA demonstrated high discriminatory power and consistency, with validation and cross-validation positive identification rates above 93% at the species level. CONCLUSION: The selected sample processing procedure can be used to identify field-collected Anopheles species, including vectors of Plasmodium, in a short period of time, with a minimal amount of tissue and without the need of an expert mosquito taxonomist. This strategy to analyse protein spectra overcomes the drawbacks of working without a reference library to classify unknown samples. Finally, this MALDI approach can aid ongoing malaria eradication efforts in Panama and other countries with large number of mosquito's species by improving vector surveillance in epidemic-prone sites such as indigenous Comarcas.

CAIM: Coverage-based Analysis for Identification of Microbiome.

Accurate taxonomic profiling of microbial taxa in a metagenomic sample is vital to gain insights into microbial ecology. Recent advancements in sequencing technologies have contributed tremendously toward understanding these microbes at species resolution through a whole shotgun metagenomic (WMS) approach. In this study, we developed a new bioinformatics tool, CAIM, for accurate taxonomic classification and quantification within both long- and short-read metagenomic samples using an alignment-based method. CAIM depends on two different containment techniques to identify species in metagenomic samples using their genome coverage information to filter out false positives rather than the traditional approach of relative abundance. In addition, we propose a nucleotide-count based abundance estimation, which yield lesser root mean square error than the traditional read-count approach. We evaluated the performance of CAIM on 28 metagenomic mock communities and 2 synthetic datasets by comparing it with other top-performing tools. CAIM maintained a consitently good performance across datasets in identifying microbial taxa and in estimating relative abundances than other tools. CAIM was then applied to a real dataset sequenced on both Nanopore (with and without amplification) and Illumina sequencing platforms and found high similality of taxonomic profiles between the sequencing platforms. Lastly, CAIM was applied to fecal shotgun metagenomic datasets of 232 colorectal cancer patients and 229 controls obtained from 4 different countries and primary 44 liver cancer patients and 76 controls. The predictive performance of models using the genome-coverage cutoff was better than those using the relative-abundance cutoffs in discriminating colorectal cancer and primary liver cancer patients from healthy controls with a highly confident species markers.

Dataset of 16S ribosomal DNA sequence-based identification of bacteriocinogenic lactic acid bacteria isolated from fermented food samples.

The dataset profiled in this research is built on sequencing of lactic acid bacteria 16S rDNA mined from Nono (N4 and N5), Kunu (K4 and K1) and Garri. The 16S rDNA sequences files are accessible under the data identification numbers: OK017047, OK017046, OK017044, OK017043, OK017045 at the GenBank database, NCBI. Taxonomic identification and phylogenetic tree analysis were done using the online BLAST (blastn) and MEGA11 software, respectively. The effect of the bacteriocin produced by these organisms on spoilage bacteria associated with salad was evaluated using an agar well diffusion assay. Limosilactobacillus pontis strain EOINONO, Limosilactobacillus pontis strain OGENONO, Limosilactobacillus pontis strain SEOGARI, Lactiplantibacillus plantarum strain MJIKUNU and Limosilactobacillus pontis strain EEIKUNU were the identified bacteriocinogenic organisms while Bacillus tequilensis strain SEOABACHA, Bacillus tequilensis strain EEIABACHA, Achromobacter xylosoxidans strain IMABACHA and Achromobacter insolitus strain MJIABACHA were the identified spoilage organisms.

Taxonomic identification and antagonistic activity of Streptomyces luomodiensis sp. nov. against phytopathogenic fungi.

Banana wilt caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) is a devastating fungal disease. Biocontrol strategies hold immense potential for inhibiting the spread of Foc TR4. Here, 30 actinobacteria were isolated from soils and screened for their antagonistic activity against Foc TR4. Strain SCA4-21T was selected due to its strongest antagonistic activity against Foc TR4. Strain SCA4-21T also exhibited strong antagonistic activity against the other eight phytopathogenic fungi. The strain was identified as the genus Streptomyces according to its physiological, biochemical, and phenotypic characteristics. The phylogenetic trees of 16S rRNA sequences demonstrated that strain SCA4-21T formed a subclade with S. iranensis HM 35T and/or S. rapamycinicus NRRL B-5491T with low bootstrap values. Considering that 16S rRNAs did not provide sufficient resolution for species-level identification, the whole genome of strain SCA4-21T was sequenced. Multilocus sequence analysis (MLSA) based on five housekeeping gene alleles (atpD, gyrB, recA, rpoB, and trpB) revealed that strain SCA4-21T clustered into S. hygroscopicus subsp. hygroscopicus NBRC 13472T with 100% of bootstrap value. The analysis of the genome-based phylogeny also approved the results. Average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) were 91.26 and 44.30%, respectively, with values below the respective species level threshold of 95 and 70%. Hence, strain SCA 4-21T represented a novel species within the genus Streptomyces, named Streptomyces luomodiensis sp. nov. The type strain is SCA4-21T (=GDMCC4.340T = JCM36555T). By the CAZymes analysis, 348 carbohydrate-active enzymes (CAZymes) were detected, including 15 chitinases and eight ß-1,3-glucanases. The fermentation broth of strain SCA4-21T, exhibiting strong antagonistic activity against Foc TR4, demonstrated high activities of chitinase and ß-1,3-glucanase, which might be involved in antifungal activity. Our results showed an innovative potential biocontrol agent for managing plant fungal diseases, specifically banana fusarium wilt.

Compacted hair in broken teeth reveals dietary prey of historic lions.

With recent advances, nuclear genome data for phylogenomic analyses can now be sequenced from minuscule quantities of DNA1 and from specimens that are more than a million years old.2 DNA analysis from hair is a well-established approach3 widely used in forensic science4 and wildlife conservation.5 Hair samples can be effectively decontaminated6 and can be used to identify the mammalian species from which the hair was shed.7,8 We aimed to use advances optimized for degraded DNA to systematically identify dietary prey species from hair compacted in the teeth of two Tsavo lions that lived during the 1890s in Kenya (see description of samples in the STAR Methods and Patterson9 and Kerbis Peterhans and Gnoske10 for background on the Tsavo "man-eaters"). Analysis of hair DNA identified giraffe, human, oryx, waterbuck, wildebeest, and zebra as prey and also identified hair that originated from lion. DNA preservation allowed for analyses of complete mitogenome profiles of zebra, giraffe, and lion. Giraffe mitogenomes are phylogeographically partitioned, and we found that the lions ate at least two individuals that belong to a subspecies of Masai giraffe (Giraffa tippelskirchi tippelskirchi) typically found in southeast Kenya. The lion mitogenome from a hair sample was identical to the Tsavo lion endogenous mitogenome and most closely matched other East African lions from Kenya and Tanzania. Our approach enables a better understanding of the hunting behaviors, diets, and ecology of historical individuals, populations, and species and holds promise for extinct populations and species.

Enhancing metagenomic classification with compression-based features.

Metagenomics is a rapidly expanding field that uses next-generation sequencing technology to analyze the genetic makeup of environmental samples. However, accurately identifying the organisms in a metagenomic sample can be complex, and traditional reference-based methods may need to be more effective in some instances. In this study, we present a novel approach for metagenomic identification, using data compressors as a feature for taxonomic classification. By evaluating a comprehensive set of compressors, including both general-purpose and genomic-specific, we demonstrate the effectiveness of this method in accurately identifying organisms in metagenomic samples. The results indicate that using features from multiple compressors can help identify taxonomy. An overall accuracy of 95% was achieved using this method using an imbalanced dataset with classes with limited samples. The study also showed that the correlation between compression and classification is insignificant, highlighting the need for a multi-faceted approach to metagenomic identification. This approach offers a significant advancement in the field of metagenomics, providing a reference-less method for taxonomic identification that is both effective and efficient while revealing insights into the statistical and algorithmic nature of genomic data. The code to validate this study is publicly available at https://github.com/ieeta-pt/xgTaxonomy.

Genetic differentiation and species diversification of the Adoxophyes orana complex (Lepidoptera: Tortricidae) in East Asia.

The Adoxophyes tea tortrix (Lepidoptera: Tortricidae) is a group of leaf rollers that cause enormous economic losses on tea and apple crops. In East Asia, taxonomic ambiguity of the Adoxophyes orana complex (AOC), which consists of A. orana, A. dubia, A. honmai, and A. paraorana, has persisted for decades because of vague diagnostic characters. In this study, differences in the AOC were examined to improve species identification, determine genetic variations, and develop control strategies. Analyses revealed that A. orana comprised 2 lineages, a widely distributed Palearctic lineage and an East Asian lineage that was nested with other Asian species. Genetic divergence of >3% is proposed to confirm the AOC species that would benefit subsequent taxonomic revision. The monophyletic Taiwanese A. sp. with 2.8-4% from other AOC species appeared to suggest it as an independent taxon, and low interspecific divergence between A. honmai and A. dubia of 0.3% indicated possibility of recent divergence or intraspecific variations. Our result further suggested that the Z9-14:Ac ratio of semiochemicals could be a reference for the reblending of pheromone attractants in Taiwanese tea plantations. Moreover, the AOC species appeared to have a tendency of specific geographic distributions, with A. dubia and A. honmai in Japan and China, A. paraorana in Korea, and A. sp. in Taiwan. Maintaining the unique genetic composition of Adoxophyes species in each geographic region and preventing the possible invasions into those AOC-free countries through the transportation of host plants are essential in managing the AOC in East Asia.

taxalogue: a toolkit to create comprehensive CO1 reference databases.

Background: Taxonomic identification through DNA barcodes gained considerable traction through the invention of next-generation sequencing and DNA metabarcoding. Metabarcoding allows for the simultaneous identification of thousands of organisms from bulk samples with high taxonomic resolution. However, reliable identifications can only be achieved with comprehensive and curated reference databases. Therefore, custom reference databases are often created to meet the needs of specific research questions. Due to taxonomic inconsistencies, formatting issues, and technical difficulties, building a custom reference database requires tremendous effort. Here, we present taxalogue, an easy-to-use software for creating comprehensive and customized reference databases that provide clean and taxonomically harmonized records. In combination with extensive geographical filtering options, taxalogue opens up new possibilities for generating and testing evolutionary hypotheses. Methods: taxalogue collects DNA sequences from several online sources and combines them into a reference database. Taxonomic incongruencies between the different data sources can be harmonized according to available taxonomies. Dereplication and various filtering options are available regarding sequence quality or metadata information. taxalogue is implemented in the open-source Ruby programming language, and the source code is available at https://github.com/nwnoll/taxalogue. We benchmark four reference databases by sequence identity against eight queries from different localities and trapping devices. Subsamples from each reference database were used to compare how well another one is covered. Results: taxalogue produces reference databases with the best coverage at high identities for most tested queries, enabling more accurate, reliable predictions with higher certainty than the other benchmarked reference databases. Additionally, the performance of taxalogue is more consistent while providing good coverage for a variety of habitats, regions, and sampling methods. taxalogue simplifies the creation of reference databases and makes the process reproducible and transparent. Multiple available output formats for commonly used downstream applications facilitate the easy adoption of taxalogue in many different software pipelines. The resulting reference databases improve the taxonomic classification accuracy through high coverage of the query sequences at high identities.

2 Hydroxybutyric Acid-Producing Bacteria in Gut Microbiome and Fusobacterium nucleatum Regulates 2 Hydroxybutyric Acid Level In Vivo.

2-hydroxybutyric acid (2HB) serves as an important regulatory factor in a variety of diseases. The circulating level of 2HB in serum is significantly higher in multiple diseases, such as cancer and type 2 diabetes (T2D). However, there is currently no systematic study on 2HB-producing bacteria that demonstrates whether gut bacteria contribute to the circulating 2HB pool. To address this question, we used BLASTP to reveal the taxonomic profiling of 2HB-producing bacteria in the human microbiome, which are mainly distributed in the phylum Proteobacteria and Firmicutes. In vitro experiments showed that most gut bacteria (21/32) have at least one path to produce 2HB, which includes Aspartic acid, methionine, threonine, and 2-aminobutyric acid. Particularly, Fusobacterium nucleatum has the strongest ability to synthesize 2HB, which is sufficient to alter colon 2HB concentration in mice. Nevertheless, neither antibiotic (ABX) nor Fusobacterium nucleatum gavage significantly affected mouse serum 2HB levels during the time course of this study. Taken together, our study presents the profiles of 2HB-producing bacteria and demonstrates that gut microbiota was a major contributor to 2HB concentration in the intestinal lumen but a relatively minor contributor to serum 2HB concentration.

A New Strategy for Microbial Taxonomic Identification through Micro-Biosynthetic Gold Nanoparticles and Machine Learning.

Microorganisms can serve as biological factories for the synthesis of inorganic nanomaterials that can become useful as nanocatalysts, energy-harvesting-storage components, antibacterial agents, and biomedical materials. Herein, the development of biosynthesis of inorganic nanomaterials into a simple, stable, and accurate strategy for distinguishing microorganisms from multiple classification levels (i.e., kingdom, order, genus, and species) without gene amplification, biochemical testing, or target recognition is reported. Gold nanoparticles (AuNPs) biosynthesized by different microorganisms differ in color of the solution, and their features can be characterized, including the particle size, the surface plasmon resonance (SPR) spectrum, and the surface potential. The inter-relation between the features of micro-biosynthetic AuNPs and the classification of microorganisms are exploited at different levels through machine learning to establish a taxonomic model. This model agrees well with traditional classification methods that offers a new strategy for microbial taxonomic identification. The underlying mechanism of this strategy is related to the biomolecules produced by different microorganisms including glucose, glutathione, and nicotinamide adenine dinucleotide phosphate-dependent reductase that regulate the features of micro-biosynthetic AuNPs. This work broadens the application of biosynthesis of inorganic materials through micro-biosynthetic AuNPs and machine learning, which holds great promise as a tool for biomedical research.

Characterizing Genomics Repositories Using Feature-Based Classification.

In the last decades, the field of metagenomics aided by NGS technologies has grown exponentially and is now a cornerstone tool in medicine. However, even with the current technologies, obtaining a conclusive identification of an organism can be challenging due to using reference-based methods. Consequently, when releasing a new repository of genomic data that contains de-novo sequences, it is problematic to characterize its content. In this paper, we propose a novel method for organism identification and the creation and characterization of genomic databases. For identification, we propose a three-step pipeline for reference-free reconstruction, reference-based classification and features-based classification. On the other hand, for content exposition and extraction, the sequences and their identification are aggregated into a web database catalogue.

Quantitative Real-Time PCR Based on SYBR Green Technology for the Identification of Philaenus italosignus Drosopoulos & Remane (Hemiptera Aphrophoridae).

The use of molecular tools to identify insect pests is a critical issue, especially when rapid and reliable tests are required. We proposed a protocol based on qPCR with SYBR Green technology to identify Philaenus italosignus (Hemiptera, Aphrophoridae). The species is one of the three spittlebugs able to transmit Xylella fastidiosa subsp. pauca ST53 in Italy, together with Philaenus spumarius and Neophilaenus campestris. Although less common than the other two species, its identification is key to verifying which role it can play when locally abundant. The proposed assay shows analytical specificity being inclusive with different populations of the target species and exclusive with non-target taxa, either taxonomically related or not. Moreover, it shows analytical sensibility, repeatability, and reproducibility, resulting in an excellent candidate for an official diagnostic method. The molecular test can discriminate P. italosignus from all non-target species, including the congeneric P. spumarius.

The Fossil Lithistida Collection at the Natural History Museum, London (UK).

Background: This paper presents a quantitative and detailed description of the Fossil Lithistida Collection in the Natural History Museum, London. This collection started to be built with the first fossil sponges from the Cretaceous of Wiltshire, collected by William Smith in 1816 and 1818 for the first geological map of England. The latest specimen to enter the collection was collected from the Permo-Carboniferous of Norway by Angela Milner, a researcher at the Museum, in 2000. Although they are mostly from the Cretaceous of England, lithistids are represented from the Cambrian to Cenozoic of England. This makes this collection key for studying this group. Lithistid study will help with understanding of biosilicification evolution in sponges to unlock the changing patterns in the silica cycle in the oceans through geological time. New information: A dataset with information about all the Fossil Lithistida Collection is available through the NHM Data Portal and Suppl. material 1. This dataset includes taxonomic identifications, registration numbers of the specimens, geographic and stratigraphic details, information about specimen collectors and donors, type status and publications where the specimens have been referred.

Global gap-analysis of amphipod barcode library.

In the age of global climate change and biodiversity loss there is an urgent need to provide effective and robust tools for diversity monitoring. One of the promising techniques for species identification is the use of DNA barcoding, that in Metazoa utilizes the so called 'gold-standard' gene of cytochrome c oxidase (COI). However, the success of this method relies on the existence of trustworthy barcode libraries of the species. The Barcode of Life Data System (BOLD) aims to provide barcodes for all existing organisms, and is complemented by the Barcode Index Number (BIN) system serving as a tool for potential species recognition. Here we provide an analysis of all public COI sequences available in BOLD of the diverse and ubiquitous crustacean order Amphipoda, to identify the barcode library gaps and provide recommendations for future barcoding studies. Our gap analysis of 25,702 records has shown that although 3,835 BINs (indicating putative species) were recognised by BOLD, only 10% of known amphipod species are represented by barcodes. We have identified almost equal contribution of both records (sequences) and BINs associated with freshwater and with marine realms. Three quarters of records have a complete species-level identification provided, while BINs have just 50%. Large disproportions between identification levels of BINs coming from freshwaters and the marine environment were observed, with three quarters of the former possessing a species name, and less than 40% for the latter. Moreover, the majority of BINs are represented by a very low number of sequences rendering them unreliable according to the quality control system. The geographical coverage is poor with vast areas of Africa, South America and the open ocean acting as "white gaps". Several, of the most species rich and highly abundant families of Amphipoda (e.g., Phoxocephalidae, Ampeliscidae, Caprellidae), have very poor representation in the BOLD barcode library. As a result of our study we recommend stronger effort in identification of already recognised BINs, prioritising the studies of families that are known to be important and abundant components of particular communities, and targeted sampling programs for taxa coming from geographical regions with the least knowledge.

Microstructural characteristics of the stony coral genus Acropora useful to coral reef paleoecology and modern conservation.

Identification of fossil corals is often limited due to poor preservation of external skeleton morphology, especially in the genus Acropora which is widespread across the Indo-Pacific. Based on skeleton characteristics from thin section, we here develop a link between the internal skeleton structure and external morphology. Ten characteristics were summarized to distinguish Acropora and five related genera, including the type and differentiation of corallites, the skeleton nature of corallites (septa, columellae, dissepiments, wall), and calcification centers within septa. Acropora is distinctive for its dimorphic corallites: axial and radial. Isopora is similar to Acropora but possess more than a single axial corallites. Montipora and Astreopora (family Acroporidae) have monomorphic corallites and a synapticular ring wall, with clustered calcification center in the former and medial lines in the latter. Pocillopora and Porties are classified by distinctive dissepiments, columellae and septa. These microstructural skeleton characteristics were effective in the genus identification of fossil corals from drilled cores in the South China Sea. Eighteen detailed characteristics (ten of axial corallites, four of radial corallites, and four of coenosteum) were used in the Acropora species classification. The axial corallites size and structure (including corallite diameter, synapticular rings, and septa), the septa of radial corallites, and the arrangement of coenosteum were critical indicators for species identification. This identification guide can help paleoenvironmental and paleoecological analyses and modern coral reef conservation and restoration.