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Monkeypox (now Mpox), a zoonotic disease caused by the monkeypox virus (MPXV) is an emerging threat to global health. In the time span of only six months, from May to October 2022, the number of MPXV cases breached 80,000 and many of the outbreaks occurred in locations that had never previously reported MPXV. Currently there are no FDA-approved MPXV-specific vaccines or treatments, therefore, finding drugs to combat MPXV is of utmost importance. The A42R profilin-like protein of the MPXV is involved in cell development and motility making it a critical drug target. A42R protein is highly conserved across orthopoxviruses, thus A42R inhibitors may work for other family members. This study sought to identify potential A42R inhibitors for MPXV treatment using computational approaches. The energy minimized 3D structure of the A42R profilin-like protein (PDB ID: 4QWO) underwent virtual screening using a library of 36,366 compounds from Traditional Chinese Medicine (TCM), AfroDb, and PubChem databases as well as known inhibitor tecovirimat via AutoDock Vina. A total of seven compounds comprising PubChem CID: 11371962, ZINC000000899909, ZINC000001632866, ZINC000015151344, ZINC000013378519, ZINC000000086470, and ZINC000095486204, predicted to have favorable binding were shortlisted. Molecular docking suggested that all seven proposed compounds have higher binding affinities to A42R (–7.2 to –8.3 kcal/mol) than tecovirimat (–6.7 kcal/mol). This was corroborated by MM/PBSA calculations, with tecovirimat demonstrating the highest binding free energy of –68.694 kJ/mol (lowest binding affinity) compared to the seven shortlisted compounds that ranged from –73.252 to –97.140 kJ/mol. Furthermore, the 7 compounds in complex with A42R demonstrated higher stability than the A42R-tecovirimat complex when subjected to 100 ns molecular dynamics simulations. The protein-ligand interaction maps generated using LigPlot+ suggested that residues Met1, Glu3, Trp4, Ile7, Arg127, Val128, Thr131, and Asn133 are important for binding. These seven compounds were adequately profiled to be potential antivirals via PASS predictions and structural similarity searches. All seven potential lead compounds were scored Pa > Pi for antiviral activity while ZINC000001632866 and ZINC000015151344 were predicted as poxvirus inhibitors with Pa values of 0.315 and 0.215, and Pi values of 0.052 and 0.136, respectively. Further experimental validations of the identified lead compounds are required to corroborate their predicted activity. These seven identified compounds represent solid footing for development of antivirals against MPXV and other orthopoxviruses.

BackgroundIn yaws-endemic areas, two-thirds of exudative cutaneous ulcers (CU) are associated with Treponema pallidum subsp. pertenue (TP) and Haemophilus ducreyi (HD); one-third are classified as idiopathic ulcers (IU). A yaws eradication campaign on Lihir Island in Papua New Guinea utilizing mass drug administration (MDA) of azithromycin initially reduced but failed to eradicate yaws; IU rates remained constant throughout the study. Using 16S rRNA gene sequencing, we previously determined that Streptococcus pyogenes was associated with some cases of IU. Here, we applied shotgun metagenomics to the same samples we analyzed previously by 16S rRNA sequencing to verify this result, identify additional IU-associated microorganisms, and determine why S. pyogenes-associated IU might have persisted after MDA of azithromycin.Methodology/principal findingsWe sequenced DNA extracted from 244 CU specimens separated into four groups based upon microorganism-specific PCR results (HD+, TP+, TP+HD+, and TP-HD- or IU). S. pyogenes was enriched in IU (24.71% relative abundance [RA]) specimens compared to other ulcer sub-groups, confirming our prior results. We bioinformatically identified the emm (M protein gene) types found in the S. pyogenes IU specimens and found matches to emm156 and emm166. Only ~39% of IU specimens contained detectable S. pyogenes, suggesting that additional organisms could be associated with IU. In the sub-set of S. pyogenes-negative IU specimens, Criibacterium bergeronii, a member of the Peptostreptococcaceae, and Fusobacterium necrophorum (7.07% versus 0.00% RA and 2.18% versus 0.00% RA, respectively), were enriched compared to the S. pyogenes-positive sub-set. Although a broad range of viruses were detected in the CU specimens, none were specifically associated with IU.Conclusions/significanceOur observations confirm the association of S. pyogenes with IU in yaws-endemic areas, and suggest that additional anaerobic bacteria, but not other microorganisms, may be associated with this syndrome. Our results should aid in the design of diagnostic tests and selective therapies for CU.

The satellite network with cache function becomes the future development trend. How to efficiently use the node cache of the satellite network has become a research hotspot. A theoretical problem that needs to be solved in the latest research on effective utilization of cache is the estimation of cache occupancy. Based on the martingale encapsulation theory, combined with the channel conditions, access protocols, and queuing strategies in the satellite storage network, a satellite node occupancy estimation method and theoretical bounds are proposed in a two-layer satellite network of GEO and LEO. The accuracy of the martingale encapsulation method in estimating the cache occupancy is estimated by simulations. The simulation results show that our method is precise. The cache occupancy estimation method we proposed provides a theoretical basis for the optimal allocation of satellite cache resources.

A microwave photonic channelizer can achieve instantaneous reception of ultra-wideband signals and effectively avoid electronic bottleneck; therefore, it can be perfectly applied to a wideband radar system and electronic warfare. In channelization schemes based on an optical frequency comb (OFC), the number of comb lines usually depends on that of the sub-channels. In order to improve the utilization rate of the comb lines of OFC, we propose a scheme to shift the frequency of OFC by using an acousto-optic frequency shifter (AOFS), which can obtain three times the number of sub-channels of the comb lines of an OFC. In order to simplify the experiment, only a three-line OFC is used in the experiment. A three-line local oscillator (LO) OFC is frequency-shifted up and down by two AOFSs, and nine optical LO signals with different frequencies are obtained, thereby realizing the simultaneous reception of eighteen sub-channels. The proposed scheme enjoys a large number of sub-channels and minimal channel crosstalk. Experimental results demonstrate that a 9-GHz bandwidth RF signal covering 10–19 GHz is divided into 18 sub-channels with a sub-bandwidth of 500 MHz. The image rejection ratio of the sub-channels is about 23 dB, and the spurious-free dynamic range (SFDR) of the receiver can reach 98 dB·Hz2/3.

ABSTRACT Urobiome research has the potential to advance the understanding of a wide range of diseases, including lower urinary tract symptoms and kidney disease. Many scientific areas have benefited from early research method consensus to facilitate the greater, common good. This consensus document, developed by a group of expert investigators currently engaged in urobiome research (UROBIOME 2020 conference participants), aims to promote standardization and advances in this field by the adoption of common core research practices. We propose a standardized nomenclature as well as considerations for specimen collection, preservation, storage, and processing. Best practices for urobiome study design include our proposal for standard metadata elements as part of core metadata collection. Although it is impractical to follow fixed analytical procedures when analyzing urobiome data, we propose guidelines to document and report data originating from urobiome studies. We offer this first consensus document with every expectation of subsequent revision as our field progresses.

Cyanobacterial macrocolonies known as Llayta are found in Andean wetlands and have been consumed since pre-Columbian times in South America. Macrocolonies of filamentous cyanobacteria are niches for colonization by other microorganisms. However, the microbiome of edible Llayta has not been explored. Based on a culture-independent approach, we report the presence, identification, and metagenomic genome reconstruction of Cyanocohniella sp. LLY associated to Llayta trichomes. The assembled genome of strain LLY is now available for further inquiries and may be instrumental for taxonomic advances concerning this genus. All known members of the Cyanocohniella genus have been isolated from salty European habitats. A biogeographic gap for the Cyanocohniella genus is partially filled by the existence of strain LLY in Andes Mountains wetlands in South America as a new habitat. This is the first genome available for members of this genus. Genes involved in primary and secondary metabolism are described, providing new insights regarding the putative metabolic capabilities of Cyanocohniella sp. LLY.

Detecting the characteristic decomposition products (SO2, SOF2, and HF) of SF6 is an effective way to diagnose the electric discharge in SF6-insulated equipment. Based on first-principles calculations, Au, Ag, and Cu were chosen as the surface modification transition metal to improve the adsorption and gas-sensing properties of MoTe2 monolayer towards SO2, SOF2, and HF gases. The results show that Au, Ag, and Cu atoms tend to be trapped by TH sites on the MoTe2 monolayer, and the binding strength increases in the order of Ag < Au < Cu. In gas adsorption, the moderate adsorption energy provides the basis that the TM-MoTe2 monolayer can be used as gas-sensing material for SO2, SOF2, and HF. The conductivity of the adsorption system changes significantly. The conductivity decreases upon gases adsorption on TM-MoTe2 monolayer, except the conductivity of Ag-MoTe2 monolayer increases after interacting with SOF2 gas.

Cutaneous ulcers (CU) affect approximately 100,000 children in the tropics each year. While two-thirds of CU are caused by Treponema pallidumpertenueHaemophilus ducreyi

The furin cleavage site in the spike glycoprotein of the SARS-CoV-2 coronavirus is considered important for the virus to enter the host cells. By analyzing 45828 SARS-CoV-2 genome sequences, we identified 103 strains of SARS-CoV-2 with various DNA mutations including 18 unique non-synonymous point mutations, one deletion, and six gains of premature stop codon that may affect the furin cleavage site. Our results revealed that the furin cleavage site might not be required for SARS-CoV-2 to enter human cells in vivo. The identified mutants may represent a new subgroup of SARS-CoV-2 coronavirus with reduced tropism and transmissibility as potential live-attenuated vaccine candidates.

With the continued spread of SARS-CoV-2 virus around the world, researchers often need to quickly identify novel mutations in newly sequenced SARS-CoV-2 genomes for studying the molecular evolution and epidemiology of the virus. We have developed a Python package, MicroGMT, which takes either raw sequence reads or assembled genome sequences as input and compares against database sequences to identify and characterize indels and point mutations. Although our default setting is optimized for SARS-CoV-2 virus, the package can be also applied to any other microbial genomes. The software is freely available at Github URL https://github.com/qunfengdong/MicroGMT.

ABSTRACT Temporal dynamics of certain human microbiotas have been described in longitudinal studies; variability often relates to modifiable factors or behaviors. Early studies of the urinary microbiota preferentially used samples obtained by transurethral catheterization to minimize vulvovaginal microbial contributions. Whereas voided specimens are preferred for longitudinal studies, the few studies that reported longitudinal data were limited to women with lower urinary tract (LUT) symptoms, due to ease of accessing a clinical population for sampling and the impracticality and risk of collecting repeated catheterized urine specimens in a nonclinical population. Here, we studied the microbiota of the LUT of nonsymptomatic, premenopausal women using midstream voided urine (MSU) specimens to investigate relationships between microbial dynamics and personal factors. Using 16S rRNA gene sequencing and a metaculturomics method called expanded quantitative urine culture (EQUC), we characterized the microbiotas of MSU and periurethral swab specimens collected daily for approximately 3 months from a small cohort of adult women. Participants were screened for eligibility, including the ability to self-collect paired urogenital specimens prior to enrollment. In this population, we found that measures of microbial dynamics related to specific participant-reported factors, particularly menstruation and vaginal intercourse. Further investigation of the trends revealed differences in the composition and diversity of LUT microbiotas within and across participants. These data, in combination with previous studies showing relationships between the LUT microbiota and LUT symptoms, suggest that personal factors relating to the genitourinary system may be an important consideration in the etiology, prevention, and/or treatment of LUT disorders. IMPORTANCE Following the discovery of the collective human urinary microbiota, important knowledge gaps remain, including the stability and variability of this microbial niche over time. Initial urinary studies preferentially utilized samples obtained by transurethral catheterization to minimize contributions from vulvovaginal microbes. However, catheterization has the potential to alter the urinary microbiota; therefore, voided specimens are preferred for longitudinal studies. In this report, we describe microbial findings obtained by daily assessment over 3 months in a small cohort of adult women. We found that, similarly to vaginal microbiotas, lower urinary tract (LUT) microbiotas are dynamic, with changes relating to several factors, particularly menstruation and vaginal intercourse. Our study results show that LUT microbiotas are both dynamic and resilient. They also offer novel opportunities to target LUT microbiotas by preventative or therapeutic means, through risk and/or protective factor modification.

Abstract Background Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers, because existing taxonomic classification tools for 16S rRNA gene sequences either do not provide species-level classification, or their classification results are unreliable. The unreliable results are due to the limitations in the existing methods which either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, or use nucleotide k-mer frequency as the proxy for sequence similarity measurement. Results We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our method does not need any training datasets specific for different taxonomic groups. Instead only a reference database is required for aligning to the query sequences, making our method easily applicable for different regions of the 16S rRNA gene or other phylogenetic marker genes. Conclusions Reliable species-level classification for 16S rRNA or other phylogenetic marker genes is critical for microbiome research. Our software shows significantly higher classification accuracy than the existing tools and we provide probabilistic-based confidence scores to evaluate the reliability of our taxonomic classification assignments based on multiple database matches to query sequences. Despite its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .

Arsenic (As), a highly toxic metalloid, naturally present in Camarones River (Atacama Desert, Chile) is a great health concern for the local population and authorities. In this study, the taxonomic and functional characterization of bacterial communities associated to metal-rich sediments from three sites of the river (sites M1, M2 and M3), showing different arsenic concentrations, were evaluated using a combination of approaches. Diversity of bacterial communities was evaluated by Illumina sequencing. Strains resistant to arsenic concentrations varying from 0.5 to 100 mM arsenite or arsenate were isolated and the presence of genes coding for enzymes involved in arsenic oxidation (aio) or reduction (arsC) investigated. Bacterial communities showed a moderate diversity which increased as arsenic concentrations decreased along the river. Sequences of the dominant taxonomic groups (abundances ≥1%) present in all three sites were affiliated to Proteobacteria (range 40.3-47.2%), Firmicutes (8.4-24.8%), Acidobacteria (10.4-17.1%), Actinobacteria (5.4-8.1%), Chloroflexi (3.9-7.5%), Planctomycetes (1.2-5.3%), Gemmatimonadetes (1.2-1.5%), and Nitrospirae (1.1-1.2%). Bacterial communities from sites M2 and M3 showed no significant differences in diversity between each other (p = 0.9753) but they were significantly more diverse than M1 (p

ABSTRACT Dysbiosis of microbial communities is associated with various human diseases, raising the possibility of using microbial compositions as biomarkers for disease diagnosis. We have developed a Bayes classifier by modeling microbial compositions with Dirichlet-multinomial distributions, which are widely used to model multicategorical count data with extra variation. The parameters of the Dirichlet-multinomial distributions are estimated from training microbiome data sets based on maximum likelihood. The posterior probability of a microbiome sample belonging to a disease or healthy category is calculated based on Bayes’ theorem, using the likelihood values computed from the estimated Dirichlet-multinomial distribution, as well as a prior probability estimated from the training microbiome data set or previously published information on disease prevalence. When tested on real-world microbiome data sets, our method, called DMBC (for Dirichlet-multinomial Bayes classifier), shows better classification accuracy than the only existing Bayesian microbiome classifier based on a Dirichlet-multinomial mixture model and the popular random forest method. The advantage of DMBC is its built-in automatic feature selection, capable of identifying a subset of microbial taxa with the best classification accuracy between different classes of samples based on cross-validation. This unique ability enables DMBC to maintain and even improve its accuracy at modeling species-level taxa. The R package for DMBC is freely available at https://github.com/qunfengdong/DMBC . IMPORTANCE By incorporating prior information on disease prevalence, Bayes classifiers have the potential to estimate disease probability better than other common machine-learning methods. Thus, it is important to develop Bayes classifiers specifically tailored for microbiome data. Our method shows higher classification accuracy than the only existing Bayesian classifier and the popular random forest method, and thus provides an alternative option for using microbial compositions for disease diagnosis.

ABSTRACT The influence of the skin microbiota on host susceptibility to infectious agents is largely unexplored. The skin harbors diverse bacterial species that may promote or antagonize the growth of an invading pathogen. We developed a human infection model for Haemophilus ducreyi in which human volunteers are inoculated on the upper arm. After inoculation, papules form and either spontaneously resolve or progress to pustules. To examine the role of the skin microbiota in the outcome of H. ducreyi infection, we analyzed the microbiomes of four dose-matched pairs of “resolvers” and “pustule formers” whose inoculation sites were swabbed at multiple time points. Bacteria present on the skin were identified by amplification and pyrosequencing of 16S rRNA genes. Nonmetric multidimensional scaling (NMDS) using Bray-Curtis dissimilarity between the preinfection microbiomes of infected sites showed that sites from the same volunteer clustered together and that pustule formers segregated from resolvers (P = 0.001, permutational multivariate analysis of variance [PERMANOVA]), suggesting that the preinfection microbiomes were associated with outcome. NMDS using Bray-Curtis dissimilarity of the endpoint samples showed that the pustule sites clustered together and were significantly different than the resolved sites (P = 0.001, PERMANOVA), suggesting that the microbiomes at the endpoint differed between the two groups. In addition to H. ducreyi, pustule-forming sites had a greater abundance of Proteobacteria, Bacteroidetes, Micrococcus, Corynebacterium, Paracoccus, and Staphylococcus species, whereas resolved sites had higher levels of Actinobacteria and Propionibacterium species. These results suggest that at baseline, resolvers and pustule formers have distinct skin bacterial communities which change in response to infection and the resultant immune response. IMPORTANCE Human skin is home to a diverse community of microorganisms, collectively known as the skin microbiome. Some resident bacteria are thought to protect the skin from infection by outcompeting pathogens for resources or by priming the immune system's response to invaders. However, the influence of the skin microbiome on the susceptibility to or protection from infection has not been prospectively evaluated in humans. We characterized the skin microbiome before, during, and after experimental inoculation of the arm with Haemophilus ducreyi in matched volunteers who subsequently resolved the infection or formed abscesses. Our results suggest that the preinfection microbiomes of pustule formers and resolvers have distinct community structures which change in response to the progression of H. ducreyi infection to abscess formation.

Resident bacterial communities (microbiota) and host antimicrobial peptides (AMPs) are both essential components of normal host innate immune responses that limit infection and pathogen induced inflammation. However, their interdependence has not been investigated in the context of urinary tract infection (UTI) susceptibility. Here, we explored the interrelationship between the urinary microbiota and host AMP responses as mechanisms for UTI risk. Using prospectively collected day of surgery (DOS) urine specimens from female pelvic floor surgery participants, we report that the relative abundance and/or frequency of specific urinary microbiota distinguished between participants who did or did not develop a post-operative UTI. Furthermore, UTI risk significantly correlated with both specific urinary microbiota and β-defensin AMP levels. Finally, urinary AMP hydrophobicity and protease activity were greater in participants who developed UTI, and correlated positively with both UTI risk and pelvic floor symptoms. These data demonstrate an interdependency between the urinary microbiota, AMP responses and symptoms, and identify a potential mechanism for UTI risk. Assessment of bacterial microbiota and host innate immune AMP responses in parallel may identify increased risk of UTI in certain populations.

Relationships between host and microbial diversity have important ecological and applied implications. Theory predicts that these relationships will depend on the spatio-temporal scale of the analysis and the niche breadth of the organisms in question, but representative data on host-microbial community assemblage in nature is lacking. We employed a natural gradient of rodent species richness and quantified bacterial communities in rodent blood at several hierarchical spatial scales to test the hypothesis that associations between host and microbial species diversity will be positive in communities dominated by organisms with broad niches sampled at large scales. Following pyrosequencing of rodent blood samples, bacterial communities were found to be comprised primarily of broad niche lineages. These communities exhibited positive correlations between host diversity, microbial diversity and the likelihood for rare pathogens at the regional scale but not at finer scales. These findings demonstrate how microbial diversity is affected by host diversity at different spatial scales and suggest that the relationships between host diversity and overall disease risk are not always negative, as the dilution hypothesis predicts.

Inflammation and infection of bovine mammary glands, commonly known as mastitis, imposes significant losses each year in the dairy industry worldwide. While several different bacterial species have been identified as causative agents of mastitis, many clinical mastitis cases remain culture negative, even after enrichment for bacterial growth. To understand the basis for this increasingly common phenomenon, the composition of bacterial communities from milk samples was analyzed using culture independent pyrosequencing of amplicons of 16S ribosomal RNA genes (16S rDNA). Comparisons were made of the microbial community composition of culture negative milk samples from mastitic quarters with that of non-mastitic quarters from the same animals. Genomic DNA from culture-negative clinical and healthy quarter sample pairs was isolated, and amplicon libraries were prepared using indexed primers specific to the V1-V2 region of bacterial 16S rRNA genes and sequenced using the Roche 454 GS FLX with titanium chemistry. Evaluation of the taxonomic composition of these samples revealed significant differences in the microbiota in milk from mastitic and healthy quarters. Statistical analysis identified seven bacterial genera that may be mainly responsible for the observed microbial community differences between mastitic and healthy quarters. Collectively, these results provide evidence that cases of culture negative mastitis can be associated with bacterial species that may be present below culture detection thresholds used here. The application of culture-independent bacterial community profiling represents a powerful approach to understand long-standing questions in animal health and disease.

Diabetes mellitus is a major risk factor for chronic periodontitis. We investigated the effects of type 2 diabetes on the subgingival plaque bacterial composition by applying culture-independent 16S rDNA sequencing to periodontal bacteria isolated from four groups of volunteers: non-diabetic subjects without periodontitis, non-diabetic subjects with periodontitis, type 2 diabetic patients without periodontitis, and type 2 diabetic patients with periodontitis. A total of 71,373 high-quality sequences were produced from the V1-V3 region of 16S rDNA genes by 454 pyrosequencing. Those 16S rDNA sequences were classified into 16 phyla, 27 classes, 48 orders, 85 families, 126 genera, and 1141 species-level OTUs. Comparing periodontally healthy samples with periodontitis samples identified 20 health-associated and 15 periodontitis-associated OTUs. In the subjects with healthy periodontium, the abundances of three genera (Prevotella, Pseudomonas, and Tannerella) and nine OTUs were significantly different between diabetic patients and their non-diabetic counterparts. In the subjects carrying periodontitis, the abundances of three phyla (Actinobacteria, Proteobacteria, and Bacteriodetes), two genera (Actinomyces and Aggregatibacter), and six OTUs were also significantly different between diabetics and non-diabetics. Our results show that type 2 diabetes mellitus could alter the bacterial composition in the subgingival plaque.

Lactobacillus-dominated vaginal microbiotas are associated with reproductive health and STI resistance in women, whereas altered microbiotas are associated with bacterial vaginosis (BV), STI risk and poor reproductive outcomes. Putative vaginal taxa have been observed in male first-catch urine, urethral swab and coronal sulcus (CS) specimens but the significance of these observations is unclear. We used 16 S rRNA sequencing to characterize the microbiota of the CS and urine collected from 18 adolescent men over three consecutive months. CS microbiotas of most participants were more stable than their urine microbiotas and the composition of CS microbiotas were strongly influenced by circumcision. BV-associated taxa, including Atopobium, Megasphaera, Mobiluncus, Prevotella and Gemella, were detected in CS specimens from sexually experienced and inexperienced participants. In contrast, urine primarily contained taxa that were not abundant in CS specimens. Lactobacilllus and Streptococcus were major urine taxa but their abundance was inversely correlated. In contrast, Sneathia, Mycoplasma and Ureaplasma were only found in urine from sexually active participants. Thus, the CS and urine support stable and distinct bacterial communities. Finally, our results suggest that the penis and the urethra can be colonized by a variety of BV-associated taxa and that some of these colonizations result from partnered sexual activity.

Urine is the CDC-recommended specimen for STI testing. It was unknown if the bacterial communities (microbiomes) in urine reflected those in the distal male urethra. We compared microbiomes of 32 paired urine and urethral swab specimens obtained from adult men attending an STD clinic, by 16S rRNA PCR and deep pyrosequencing. Microbiomes of urine and swabs were remarkably similar, regardless of STI status of the subjects. Thus, urine can be used to characterize urethral microbiomes when swabs are undesirable, such as in population-based studies of the urethral microbiome or where multiple sampling of participants is required.

BackgroundThe microbiome of the male urogenital tract is poorly described but it has been suggested that bacterial colonization of the male urethra might impact risk of sexually transmitted infection (STI). Previous cultivation-dependent studies showed that a variety of non-pathogenic bacteria colonize the urethra but did not thoroughly characterize these microbiomes or establish links between the compositions of urethral microbiomes and STI.Methodology/findingsHere, we used 16S rRNA PCR and sequencing to identify bacteria in urine specimens collected from men who lacked symptoms of urethral inflammation but who differed in status for STI. All of the urine samples contained multiple bacterial genera and many contained taxa that colonize the human vagina. Uncultivated bacteria associated with female genital tract pathology were abundant in specimens from men who had STI.ConclusionsUrine microbiomes from men with STI were dominated by fastidious, anaerobic and uncultivated bacteria. The same taxa were rare in STI negative individuals. Our findings suggest that the composition of male urine microbiomes is related to STI.

Monkeypox (now Mpox), a zoonotic disease caused by the monkeypox virus (MPXV) is an emerging threat to global health. In the time span of only six months, from May to October 2022, the number of MPXV cases breached 80,000 and many of the outbreaks occurred in locations that had never previously reported MPXV. Currently there are no FDA-approved MPXV-specific vaccines or treatments, therefore, finding drugs to combat MPXV is of utmost importance. The A42R profilin-like protein of the MPXV is involved in cell development and motility making it a critical drug target. A42R protein is highly conserved across orthopoxviruses, thus A42R inhibitors may work for other family members. This study sought to identify potential A42R inhibitors for MPXV treatment using computational approaches. The energy minimized 3D structure of the A42R profilin-like protein (PDB ID: 4QWO) underwent virtual screening using a library of 36,366 compounds from Traditional Chinese Medicine (TCM), AfroDb, and PubChem databases as well as known inhibitor tecovirimat via AutoDock Vina. A total of seven compounds comprising PubChem CID: 11371962, ZINC000000899909, ZINC000001632866, ZINC000015151344, ZINC000013378519, ZINC000000086470, and ZINC000095486204, predicted to have favorable binding were shortlisted. Molecular docking suggested that all seven proposed compounds have higher binding affinities to A42R (-7.2 to -8.3 kcal/mol) than tecovirimat (-6.7 kcal/mol). This was corroborated by MM/PBSA calculations, with tecovirimat demonstrating the highest binding free energy of - 68.694 kJ/mol (lowest binding affinity) compared to the seven shortlisted compounds that ranged from -73.252 to -97.140 kJ/mol. Furthermore, the 7 compounds in complex with A42R demonstrated higher stability than the A42Rtecovirimat complex when subjected to 100 ns molecular dynamics simulations. The protein-ligand interaction maps generated using LigPlot+ suggested that residues Met; Glu3, Trp4, Ile7, Arg127, Val128, Thr131, and Asn133 are important for binding. These seven compounds were adequately profiled to be potential antivirals via PASS predictions and structural similarity searches. All seven potential lead compounds were scored Pa > Pi for antiviral activity while ZINC000001632866 and ZINC000015151344 were predicted as poxvirus inhibitors with Pa values of 0.315 and 0.215, and Pi values of 0.052 and 0.136, respectively. Further experimental validations of the identified lead compounds are required to corroborate their predicted activity. These seven identified compounds represent solid footing for development of antivirals against MPXV and other orthopoxviruses. [ABSTRACT FROM AUTHOR]