HCV prevalence and phylogenetic characteristics in a cross-sectional, community study of young people who inject drugs in New York City: Opportunity for and threats to HCV elimination.

Background and Aims: In the United States, the opioid epidemic has led many young people who use opioids to initiate injection drug use, putting them at risk for hepatitis C virus (HCV) infection. However, community surveys to monitor HCV prevalence among young people who inject drugs (YPWID) are rare. Methods: As part of Staying Safe (Ssafe), a trial to evaluate an HCV-prevention intervention, a community-recruited sample of 439 young people who use opioids (ages 18-30) in New York City (NYC) were screened from 2018 to 2021. Screening procedures included a brief verbal questionnaire, a visual check for injection marks, onsite urine drug testing, rapid HCV antibody (Ab) testing, and dried blood spot (DBS) collection. DBS specimens were sent to a laboratory for HCV RNA testing and phylogenetic analysis to identify genetic linkages among HCV RNA-positive specimens. Multivariable logistic regression was used to assess associations between HCV status (Ab and RNA) and demographics and drug use patterns. Results: Among the 330 participants who reported injecting drugs (past 6 months), 33% (n = 110) tested HCV Ab-positive, 58% of whom (n = 64) had HCV RNA-positive DBS specimens, indicating active infection. In multivariable analysis, visible injection marks (AOR = 3.02; p < 0.001), older age (AOR = 1.38; p < 0.05), and female gender (AOR = 1.69; p = 0.052) were associated with HCV Ab-positive status. Visible injection marks were also associated with HCV RNA-positive status (AOR = 5.24; p < 0.01). Twenty-five percent of RNA-positive specimens (14/57) were genetically linked. Conclusion: The relatively low prevalence of active infection suggests the potential impact of treatment-as-prevention in reducing HCV prevalence among YPWID. Targeted community serosurveys could help identify actively infected YPWID for treatment, thereby reducing HCV incidence and future transmissions.

Inferring the Evolutionary Model of Community-Structuring Traits with Convolutional Kitchen Sinks.

When communities are assembled through processes such as filtering or limiting similarity acting on phylogenetically conserved traits, the evolutionary signature of those traits may be reflected in patterns of community membership. We show how the model of trait evolution underlying community-structuring traits can be inferred from community membership data using both a variation of a traditional eco-phylogenetic metric-the mean pairwise distance (MPD) between taxa-and a recent machine learning tool, Convolutional Kitchen Sinks (CKS). Both methods perform well across a range of phylogenetically informative evolutionary models, but CKS outperforms MPD as tree size increases. We demonstrate CKS by inferring the evolutionary history of freeze tolerance in angiosperms. Our analysis is consistent with a late burst model, suggesting freeze tolerance evolved recently. We suggest that multiple data types that are ordered on phylogenies, such as trait values, species interactions, or community presence/absence, are good candidates for CKS modeling because the generative models produce structured differences between neighboring points that CKS is well-suited for. We introduce the R package kitchen to perform CKS for generic application of the technique.

Crocosphaera watsonii - A widespread nitrogen-fixing unicellular marine cyanobacterium.

Crocosphaera watsonii is a unicellular N2-fixing (diazotrophic) cyanobacterium observed in tropical and subtropical oligotrophic oceans. As a diazotroph, it can be a source of bioavailable nitrogen (N) to the microbial community in N-limited environments, and this may fuel primary production in the regions where it occurs. Crocosphaera watsonii has been the subject of intense study, both in culture and in field populations. Here, we summarize the current understanding of the phylogenetic and physiological diversity of C. watsonii, its distribution, and its ecological niche. Analysis of the relationships among the individual Crocosphaera species and related free-living and symbiotic lineages of diazotrophs based on the nifH gene have shown that the C. watsonii group holds a basal position and that its sequence is more similar to Rippkaea and Zehria than to other Crocosphaera species. This finding warrants further scrutiny to determine if the placement is related to a horizontal gene transfer event. Here, the nifH UCYN-B gene copy number from a recent synthesis effort was used as a proxy for relative C. watsonii abundance to examine patterns of C. watsonii distribution as a function of environmental factors, like iron and phosphorus concentration, and complimented with a synthesis of C. watsonii physiology. Furthermore, we have summarized the current knowledge of C. watsonii with regards to N2 fixation, photosynthesis, and quantitative modeling of physiology. Because N availability can limit primary production, C. watsonii is widely recognized for its importance to carbon and N cycling in ocean ecosystems, and we conclude this review by highlighting important topics for further research on this important species.

Leveraging phylogenetic signal to unravel microbiome function and assembly rules.

Clarifying the general rules behind microbial community assembly will foster the development of microbiome-based technological solutions. Here, we study microbial community assembly through a computational analysis of phylogenetic core groups (PCGs): discrete portions of the bacterial phylogeny with high prevalence in the ecosystem under study. We first show that the existence of PCGs was a predominant feature of the varied set of microbial ecosystems studied. Then, we re-analyzed an in vitro experimental dataset using a PCG-based approach, drawing only from its community composition data and from publicly available genomic databases. Using mainly genome scale metabolic models and population dynamics modeling, we obtained ecological insights on metabolic niche structure and population dynamics comparable to those gained after canonical experimentation. Thus, leveraging phylogenetic signal to help unravel microbiome function and assembly rules offers a potential avenue to gain further insight on Earth's microbial ecosystems.

Salinity-triggered homogeneous selection constrains the microbial function and stability in lakes.

Climate change and anthropogenic exploitation have led to the gradual salinization of inland waters worldwide. However, the impacts of this process on the prokaryotic plankton communities and their role in biogeochemical cycles in the inland lake are poorly known. Here, we take a space-for-time substitution approach, using 16S rRNA gene amplicon sequencing and metagenomic sequencing. We analyzed the prokaryotic plankton communities of 11 lakes in northwest China, with average water salinities ranging from 0.002 to 14.370%. The results demonstrated that, among the various environmental parameters, salinity was the most important driver of prokaryotic plankton ß-diversity (Mantel test, r = 0.53, P < 0.001). (1) Under low salinity, prokaryotic planktons were assembled by stochastic processes and employed diverse halotolerant strategies, including the synthesis and uptake of compatible solutes and extrusion of Na+ or Li+ in exchange for H+. Under elevated salinity pressure, strong homogeneous selection meant that only planktonic prokaryotes showing an energetically favorable halotolerant strategy employing an Mnh-type Na+/H+ antiporter remained. (2) The decreasing taxonomic diversity caused by intense environmental filtering in high-salinity lakes impaired functional diversity related to substance metabolism. The prokaryotes enhanced the TCA cycle, carbon fixation, and low-energy-consumption amino acid biosynthesis in high-salinity lakes. (3) Elevated salinity pressure decreased the negative:positive cohesion and the modularity of the molecular ecology networks for the planktonic prokaryotes, indicating a precarious microbial network. Our findings provide new insights into plankton ecology and are helpful for the protecting of the biodiversity and function of inland lakes against the background of salinization. KEY POINTS: • Increased salinity enhances homogeneous selection in the microbial assembly. • Elevated salinity decreases the microbial co-occurrence networks stability. • High salinity damages the microbial function diversity.

Association of demographics, HCV co-infection, HIV-1 subtypes and genetic clustering with late HIV diagnosis: a retrospective analysis from the Japanese Drug Resistance HIV-1 Surveillance Network.

INTRODUCTION: Late diagnosis of the human immunodeficiency virus (HIV) is a major concern epidemiologically, socially and for national healthcare systems. Although the association of certain demographics with late HIV diagnosis has been reported in several studies, the association of other factors, including clinical and phylogenetic factors, remains unclear. In the present study, we conducted a nationwide analysis to explore the association of demographics, clinical factors, HIV-1 subtypes/circulating recombinant form (CRFs) and genetic clustering with late HIV diagnosis in Japan, where new infections mainly occur among young men who have sex with men (MSM) in urban areas. METHODS: Anonymized data on demographics, clinical factors and HIV genetic sequences from 39.8% of people newly diagnosed with HIV in Japan were collected by the Japanese Drug Resistance HIV-1 Surveillance Network from 2003 to 2019. Factors associated with late HIV diagnosis (defined as HIV diagnosis with a CD4 count <350 cells/µl) were identified using logistic regression. Clusters were identified by HIV-TRACE with a genetic distance threshold of 1.5%. RESULTS: Of the 9422 people newly diagnosed with HIV enrolled in the surveillance network between 2003 and 2019, 7752 individuals with available CD4 count at diagnosis were included. Late HIV diagnosis was observed in 5522 (71.2%) participants. The overall median CD4 count at diagnosis was 221 (IQR: 62-373) cells/µl. Variables independently associated with late HIV diagnosis included age (adjusted odds ratio [aOR] 2.21, 95% CI 1.88-2.59, ≥45 vs. ≤29 years), heterosexual transmission (aOR 1.34, 95% CI 1.11-1.62, vs. MSM), living outside of Tokyo (aOR 1.18, 95% CI 1.05-1.32), hepatitis C virus (HCV) co-infection (aOR 1.42, 95% CI 1.01-1.98) and not belonging to a cluster (aOR 1.30, 95% CI 1.12-1.51). CRF07_BC (aOR 0.34, 95% CI 0.18-0.65, vs. subtype B) was negatively associated with late HIV diagnosis. CONCLUSIONS: In addition to demographic factors, HCV co-infection, HIV-1 subtypes/CRFs and not belonging to a cluster were independently associated with late HIV diagnosis in Japan. These results imply the need for public health programmes aimed at the general population, including but not limited to key populations, to encourage HIV testing.

Bioinformatic analysis of the coding region of the melatonin receptor 1b gene as a reliable DNA marker to resolve interspecific mammal phylogenetic relationships.

This research looks into the main DNA markers and the limits of their application in molecular phylogenetic analysis. Melatonin 1B (MTNR1B) receptor genes were analyzed from various biological sources. Based on the coding sequences of this gene, using the class Mammalia as example, phylogenetic reconstructions were made to study the potential of mtnr1b as a DNA marker for phylogenetic relationships investigating. The phylogenetic trees were constructed using NJ, ME and ML methods that establish the evolutionary relationships between different groups of mammals. The resulting topologies were generally in good agreement with topologies established on the basis of morphological and archaeological data as well as with other molecular markers. The present divergences provided a unique opportunity for evolutionary analysis. These results suggest that the coding sequence of the MTNR1B gene can be used as a marker to study the relationships of lower evolutionary levels (order, species) as well as to resolve deeper branches of the phylogenetic tree at the infraclass level.

Nanopore-only assemblies for genomic surveillance of the global priority drug-resistant pathogen, Klebsiella pneumoniae.

Oxford Nanopore Technologies (ONT) sequencing has rich potential for genomic epidemiology and public health investigations of bacterial pathogens, particularly in low-resource settings and at the point of care, due to its portability and affordability. However, low base-call accuracy has limited the reliability of ONT data for critical tasks such as antimicrobial resistance (AMR) and virulence gene detection and typing, serotype prediction, and cluster identification. Thus, Illumina sequencing remains the standard for genomic surveillance despite higher capital and running costs. We tested the accuracy of ONT-only assemblies for common applied bacterial genomics tasks (genotyping and cluster detection, implemented via Kleborate, Kaptive and Pathogenwatch), using data from 54 unique Klebsiella pneumoniae isolates. ONT reads generated via MinION with R9.4.1 flowcells were basecalled using three alternative models [Fast, High-accuracy (HAC) and Super-accuracy (SUP), available within ONT's Guppy software], assembled with Flye and polished using Medaka. Accuracy of typing using ONT-only assemblies was compared with that of Illumina-only and hybrid ONT+Illumina assemblies, constructed from the same isolates as reference standards. The most resource-intensive ONT-assembly approach (SUP basecalling, with or without Medaka polishing) performed best, yielding reliable capsule (K) type calls for all strains (100 % exact or best matching locus), reliable multi-locus sequence type (MLST) assignment (98.3 % exact match or single-locus variants), and good detection of acquired AMR genes and mutations (88-100 % correct identification across the various drug classes). Distance-based trees generated from SUP+Medaka assemblies accurately reflected overall genetic relationships between isolates. The definition of outbreak clusters from ONT-only assemblies was problematic due to inflation of SNP counts by high base-call errors. However, ONT data could be reliably used to 'rule out' isolates of distinct lineages from suspected transmission clusters. HAC basecalling + Medaka polishing performed similarly to SUP basecalling without polishing. Therefore, we recommend investing compute resources into basecalling (SUP model), wherever compute resources and time allow, and note that polishing is also worthwhile for improved performance. Overall, our results show that MLST, K type and AMR determinants can be reliably identified with ONT-only R9.4.1 flowcell data. However, cluster detection remains challenging with this technology.

HAPPE: A Tool for Population Haplotype Analysis and Visualization in Editable Excel Tables.

Haplotype identification, characterization and visualization are important for large-scale analysis and use in population genomics. Many tools have been developed to visualize haplotypes, but it is challenging to display both the pattern of haplotypes and the genotypes for each single SNP in the context of a large amount of genomic data. Here, we describe the tool HAPPE, which uses the agglomerative hierarchical clustering algorithm to characterize and visualize the genotypes and haplotypes in a phylogenetic context. The tool displays the plots by coloring the cells and/or their borders in Excel tables for any given gene and genomic region of interest. HAPPE facilitates informative displays wherein data in plots are easy to read and access. It allows parallel display of several lines of values, such as phylogenetic trees, P values of GWAS, the entry of genes or SNPs, and the sequencing depth at each position. These features are informative for the detection of insertion/deletions or copy number variations. Overall, HAPPE provides editable plots consisting of cells in Excel tables, which are user-friendly to non-programmers. This pipeline is coded in Python and is available at https://github.com/fengcong3/HAPPE.

Concordance of HIV transmission risk factors elucidated using viral diversification rate and phylogenetic clustering.

BACKGROUND AND OBJECTIVES: Although HIV sequence clustering is routinely used to identify subpopulations experiencing elevated transmission, it over-simplifies transmission dynamics and is sensitive to methodology. Complementarily, viral diversification rates can be used to approximate historical transmission rates. Here, we investigated the concordance and sensitivity of HIV transmission risk factors identified by phylogenetic clustering, viral diversification rate, changes in viral diversification rate and a combined approach. METHODOLOGY: Viral sequences from 9848 people living with HIV in British Columbia, Canada, sampled between 1996 and February 2019, were used to infer phylogenetic trees, from which clusters were identified and viral diversification rates of each tip were calculated. Factors associated with heightened transmission risk were compared across models of cluster membership, viral diversification rate, changes in diversification rate, and viral diversification rate among clusters. RESULTS: Viruses within larger clusters had higher diversification rates and lower changes in diversification rate than those within smaller clusters; however, rates within individual clusters, independent of size, varied widely. Risk factors for both cluster membership and elevated viral diversification rate included being male, young, a resident of health authority E, previous injection drug use, previous hepatitis C virus infection or a high recent viral load. In a sensitivity analysis, models based on cluster membership had wider confidence intervals and lower concordance of significant effects than viral diversification rate for lower sampling rates. CONCLUSIONS AND IMPLICATIONS: Viral diversification rate complements phylogenetic clustering, offering a means of evaluating transmission dynamics to guide provision of treatment and prevention services. LAY SUMMARY: Understanding HIV transmission dynamics within clusters can help prioritize public health resource allocation. We compared socio-demographic and clinical risk factors associated with phylogenetic cluster membership and viral diversification rate, a historical branching rate, in order to assess their relative concordance and sampling sensitivity.

The adaptive challenge of extreme conditions shapes evolutionary diversity of plant assemblages at continental scales.

The tropical conservatism hypothesis (TCH) posits that the latitudinal gradient in biological diversity arises because most extant clades of animals and plants originated when tropical environments were more widespread and because the colonization of colder and more seasonal temperate environments is limited by the phylogenetically conserved environmental tolerances of these tropical clades. Recent studies have claimed support of the TCH, indicating that temperate plant diversity stems from a few more recently derived lineages that are nested within tropical clades, with the colonization of the temperate zone being associated with key adaptations to survive colder temperatures and regular freezing. Drought, however, is an additional physiological stress that could shape diversity gradients. Here, we evaluate patterns of evolutionary diversity in plant assemblages spanning the full extent of climatic gradients in North and South America. We find that in both hemispheres, extratropical dry biomes house the lowest evolutionary diversity, while tropical moist forests and many temperate mixed forests harbor the highest. Together, our results support a more nuanced view of the TCH, with environments that are radically different from the ancestral niche of angiosperms having limited, phylogenetically clustered diversity relative to environments that show lower levels of deviation from this niche. Thus, we argue that ongoing expansion of arid environments is likely to entail higher loss of evolutionary diversity not just in the wet tropics but in many extratropical moist regions as well.

Dredging alleviates cyanobacterial blooms by weakening diversity maintenance of bacterioplankton community.

Disentangling ecological mechanisms behind dredging is meaningful to implement environmental policy for improving water quality. However, environmental adaptation and community assembly processes of bacterioplankton in response to dredging disturbance are poorly understood. Based on Illumine MiSeq sequencing and multiple statistical analyses, we estimated interactions, functions, environmental breadths, phylogenetic signals, phylogenetic clustering, and ecological assembly processes of bacterioplankton community before and after dredging. We found distinct change in community composition, comparable decreases in diversity, functional redundancy and conflicting interaction, relatively low phylogenetic clustering, and relatively weak environmental adaptation after dredging. The bacterioplankton community assembly was affected by both stochastic and deterministic processes before dredging, but dominated by stochasticity after dredging. Sediment total phosphorus was a decisive factor in balancing determinism and stochasticity for bacterioplankton community assembly before and after dredging. Consequently, taxonomic and phylogenetic α-diversities of bacterioplankton exhibited higher contributions to the water trophic level represented by chlorophyl α before dredging than afterwards. Our results emphasized bacterioplankton in response to environmental changes caused by dredging, with nutrient loss and ecological drift playing important roles. These findings extend knowledge of contribution of bacterioplankton diversity to water trophic level and decipher mechanisms of bacterioplankton diversity maintenance in response to dredging, which is useful for guiding mitigation of cyanobacterial blooms.

Bridging Rare and Abundant Bacteria with Ecosystem Multifunctionality in Salinized Agricultural Soils: from Community Diversity to Environmental Adaptation.

Bacterial diversity and ecosystem multifunctionality (EMF) vary along environmental gradients. However, little is known about interconnections between EMF and taxonomic and phylogenetic diversities of rare and abundant bacteria. Using MiSeq sequencing and multiple statistical analyses, we evaluated the maintenance of taxonomic and phylogenetic diversities of rare and abundant bacteria and their contributions to EMF in salinized agricultural soils (0.09 to 19.91 dS/m). Rare bacteria exhibited closer phylogenetic clustering and broader environmental breadths than abundant ones, while abundant bacteria showed higher functional redundancies and stronger phylogenetic signals of ecological preferences than rare ones. Variable selection (86.7%) dominated rare bacterial community assembly, and dispersal limitation (54.7%) and variable selection (24.5%) determined abundant bacterial community assembly. Salinity played a decisive role in mediating the balance between stochastic and deterministic processes and showed significant effects on functions and diversities of both rare and abundant bacteria. Rare bacterial taxonomic α-diversity and abundant bacterial phylogenetic α-diversity contributed significantly to EMF, while abundant bacterial taxonomic α-diversity and rare bacterial phylogenetic α-diversity did not. Additionally, abundant rather than rare bacterial community function had a significant effect on soil EMF. These findings extend our knowledge of environmental adaptation of rare and abundant bacteria and highlight different contributions of taxonomic and phylogenetic α-diversities of rare and abundant bacteria to soil EMF.IMPORTANCE Soil salinization is a worldwide environmental problem and threatens plant productivity and microbial diversity. Understanding the generation and maintenance of microbial diversity is essential to estimate soil tillage potential via investigating ecosystem multifunctionality. Our sequence-based data showed differences in environmental adaptations of rare and abundant bacteria at taxonomic and phylogenetic levels, which led to different contributions of taxonomic and phylogenetic α-diversities of rare and abundant bacteria to soil EMF. Studying the diversity of rare and abundant bacteria and their contributions to EMF in salinized soils is critical for guiding soil restoration.

Temperature and microbial interactions drive the deterministic assembly processes in sediments of hot springs.

Terrestrial geothermal ecosystems, as a representative of extreme environments, exhibit a variety of geochemical gradients, and their microbes are thought to be under high stress through environmental selection. However, it is still unclear how stochasticity and biotic interactions contribute to the microbial community assembly in hot springs. Here, we investigated the assembly processes and co-occurrence patterns of microbiota (i.e. bacteria and archaea) in both water and sediments sampled from fifteen hot springs in the Tengchong area, Southwestern of China, using 16S rRNA gene sequencing combined with multivariate ecological and statistical methods. These hot springs harbored more specialists than non-geothermal ecosystems, which are well-adapted to the extreme conditions, as shown by extremely high nearest-taxon index (NTI) and narrower niche width. Habitat differentiation led to the differences in microbial diversity, species-interactions, and community assembly between water and sediment communities. The sediment community showed stronger phylogenetic clustering and was primarily governed by heterogeneous selection, while undominated stochastic processes and dispersal limitation were the major assembly processes in the water community. Temperature and ferrous iron were the major factors mediating the balance of stochastic and deterministic assembly processes in sediment communities, as evidenced by how divergences in temperature and ferrous iron increased the proportion of determinism. Microbial interactions in sediments contributed to deterministic community assembly, as indicated by more complex associations and greater responsiveness to environmental change than water community. These findings uncover the ecological processes underlying microbial communities in hot springs, and provide potential insight into understanding the mechanism to maintain microbial diversity in extreme biospheres.

Large transmission cluster of acute hepatitis C identified among HIV-positive men who have sex with men in Bangkok, Thailand.

A rapidly emerging and highly concentrated hepatitis C virus (HCV) outbreak has recently been observed among both acute and chronic HIV-positive men who have sex with men (MSM) in Bangkok, Thailand. NS5B regions of the HCV genome were amplified using nested PCR and sequenced. Phylogenetic inference was constructed by Maximum Likelihood methods and clusters were identified with support and genetic distance thresholds of 85% and of 4.5%. Forty-eight (25 acute HIV and 23 chronic HIV) MSM with incident HCV infection were included in the analysis. HCV genotype (GT) was 85% GT 1a and 15% GT 3a or 3b. Median age at HCV diagnosis was 34 (interquartile range, 28-41) years. 83.3% (40/48) had history of syphilis infection and 36% (16/44) reported crystal methamphetamine use. Only 2 (4%) reported ever injecting drugs, both crystal methamphetamine. In the phylogenetic clustering analysis, 83% belonged to one of two clusters: one large (75%) and one small (8%) cluster. All clusters were GT 1a. MSM with acute HIV infection were more likely to be in a cluster (92%) than those with chronic infection (74%). HCV screening should be regularly performed for MSM in ART clinics, and offering direct-acting antiviral agents to all MSM with HCV infection might contain the HCV epidemic from expanding further.

Phylogenetic distribution of the bacteriocin repertoire of lactic acid bacteria species associated with artisanal cheese.

The microbiota contributes to artisanal cheese bioprotection and biopreservation through inter and intraspecific competition. This work aimed to investigate the phylogenetic distribution of the repertoire of bacteriocin structural genes of model lactic acid bacteria (LAB) in order to investigate its respective role in the artisanal cheeses microenvironment. A phylogenetic analysis of the rRNA 16S gene from 445 model strains of LAB was conducted using bayesian inference and the repertoire of bacteriocin genes was predicted from these strains by BAGEL software. Bacterial strains were clustered in five monophyletic clades (A, B, C, D and E) with high posterior probability values (PP > 0.99). One bacteriocin structural gene was predicted for 88.5% of the analyzed strains. The majority of the species encoded different classes of bacteriocins. Greater diversity of bacteriocin genes was found for strains included in clade A, comprising Lactococcus lactis, Streptococcus agalactiae, Streptococcus thermophilus, Streptococcus macedonicus, Enterococcus faecalis and Enterococcus faecium. In addition, Lactococcus lactis presented higher diversity of bacteriocin classes, encoding glycocins, lanthipeptides, sactipeptides, cyclic and linear azole-containing peptides, included in bacteriocins class I, besides class II and III. The results suggest that the distribution of bacteriocin structural genes is related to the phylogenetic clades of LAB species, with a higher frequency in some specific clades. Information comprised in this study contributes to comprehend the bacterial competition mechanisms in the artisanal cheese microenvironment.

Phylogeny of Diplazium (Athyriaceae) revisited: Resolving the backbone relationships based on plastid genomes and phylogenetic tree space analysis.

Despite progress in resolving the phylogeny of twinsorus ferns (Diplazium) based on multilocus phylogenetic studies, uncertainty remains especially for deep, or backbone relationships among closely related clades, suggesting a classic case of rapid evolutionary radiation. Here, we investigated the deep phylogenetic relationships within Diplazium by sampling all major clades and using 51 plastid genomes (plastomes), of which 38 were newly sequenced with high-throughput sequencing technology, resulting more than 127,000 informative sites. Using parsimony, maximum likelihood and Bayesian analyses of plastome sequences, we largely resolved the backbone of the phylogeny of Diplazium with strong support. However, we also detected phylogenetic incongruence among different datasets and moderately to poorly supported relationships, particularly at several extremely short internal branches. By using phylogenetic tree space and topology-clustering analyses, we provide evidence that conflicting phylogenetic signals can be found across the trees estimated from individual chloroplast protein-coding genes, which may underlie the difficulty of systematics of Diplazium. Furthermore, our phylogenetic estimate offers more resolution over previous multilocus analyses, providing a framework for future taxonomic revisions of sectional classification of Diplazium. Our study demonstrates the advantage of a character-rich plastome dataset, combining the comparison of different phylogenetic methods, for resolving the recalcitrant lineages that have undergone rapid radiation and dramatic changes in evolutionary rates.

Inferring putative transmission clusters with Phydelity.

Current phylogenetic clustering approaches for identifying pathogen transmission clusters are limited by their dependency on arbitrarily defined genetic distance thresholds for within-cluster divergence. Incomplete knowledge of a pathogen's underlying dynamics often reduces the choice of distance threshold to an exploratory, ad hoc exercise that is difficult to standardise across studies. Phydelity is a new tool for the identification of transmission clusters in pathogen phylogenies. It identifies groups of sequences that are more closely related than the ensemble distribution of the phylogeny under a statistically principled and phylogeny-informed framework, without the introduction of arbitrary distance thresholds. Relative to other distance threshold- and model-based methods, Phydelity outputs clusters with higher purity and lower probability of misclassification in simulated phylogenies. Applying Phydelity to empirical datasets of hepatitis B and C virus infections showed that Phydelity identified clusters with better correspondence to individuals that are more likely to be linked by transmission events relative to other widely used non-parametric phylogenetic clustering methods without the need for parameter calibration. Phydelity is generalisable to any pathogen and can be used to identify putative direct transmission events. Phydelity is freely available at https://github.com/alvinxhan/Phydelity.

Highly sensitive parechovirus CODEHOP PCR amplification of the complete VP1 gene for typing directly from clinical specimens and correct typing based on phylogenetic clustering.

PURPOSE: Human parechoviruses (HPeVs), particularly type 3, can cause severe neurological disease and neonatal sepsis in infants. HPeV3 lacks the receptor-binding motif arginine-glycine aspartic acid (RGD), and is proposed to use a different receptor associated with severe disease. In contrast, HPeV1, which contains the RGD motif, is associated with mild disease. Rapid characterization of the presence/absence of this motif is essential for understanding their epidemiology and differential disease profiles. Current HPeV typing assays are based on partial capsid genes and often do not encompass the C-terminus where the RGD region is localized/absent. In addition, these assays lack sensitivity to enable characterization within low viral-load samples, such as cerebral spinal fluid. METHODOLOGY: We developed a highly sensitive HPeV CODEHOP PCR, which enables typing of parechoviruses directly from clinical samples while generating a complete VP1 gene, including the C-terminus. RESULTS: The assay was HPeV-specific and has a sensitivity of 6.3 TCID50 ml-1 for HPeV1 and 0.63 TCID50 ml-1 for HPeV3. Analysis of the complete VP1 gene in comparison to partial VP1 fragments generated by previously published PCRs showed homologous clustering for most types. However, phylogenetic analysis of partial VP1 fragments showed incongruent typing based on the 75  % homology classification rule. In particular, the strains designated as type 17 were found to be either type 3 or 4 when using the (near-) complete VP1 fragment. CONCLUSION: While enabling sensitive characterization of HPeVs directly from clinical samples, the HPeV CODEHOP PCR enables the characterization of RGD and non-RGD strains and correct HPeV typing based on the complete VP1.

Phylogenetic Clustering by Linear Integer Programming (PhyCLIP).

Subspecies nomenclature systems of pathogens are increasingly based on sequence data. The use of phylogenetics to identify and differentiate between clusters of genetically similar pathogens is particularly prevalent in virology from the nomenclature of human papillomaviruses to highly pathogenic avian influenza (HPAI) H5Nx viruses. These nomenclature systems rely on absolute genetic distance thresholds to define the maximum genetic divergence tolerated between viruses designated as closely related. However, the phylogenetic clustering methods used in these nomenclature systems are limited by the arbitrariness of setting intra and intercluster diversity thresholds. The lack of a consensus ground truth to define well-delineated, meaningful phylogenetic subpopulations amplifies the difficulties in identifying an informative distance threshold. Consequently, phylogenetic clustering often becomes an exploratory, ad hoc exercise. Phylogenetic Clustering by Linear Integer Programming (PhyCLIP) was developed to provide a statistically principled phylogenetic clustering framework that negates the need for an arbitrarily defined distance threshold. Using the pairwise patristic distance distributions of an input phylogeny, PhyCLIP parameterizes the intra and intercluster divergence limits as statistical bounds in an integer linear programming model which is subsequently optimized to cluster as many sequences as possible. When applied to the hemagglutinin phylogeny of HPAI H5Nx viruses, PhyCLIP was not only able to recapitulate the current WHO/OIE/FAO H5 nomenclature system but also further delineated informative higher resolution clusters that capture geographically distinct subpopulations of viruses. PhyCLIP is pathogen-agnostic and can be generalized to a wide variety of research questions concerning the identification of biologically informative clusters in pathogen phylogenies. PhyCLIP is freely available at http://github.com/alvinxhan/PhyCLIP, last accessed March 15, 2019.