Search bioRxiv⌕ Search

Biology subjects

Zhao, L.

Publications and source records attributed to Zhao, L..

At least 217 records · Page 12Linked to original sources
bioRxiv2023

A non-canonical function of LDHB promotes SLC7A11-mediated glutathione metabolism and protects against glutaminolysis-dependent ferroptosis in KRAS-driven lung cancer

Ferroptosis, a form of non-apoptotic cell death program driven by excessive lipid peroxidation and an important mechanism of tumor suppression, is frequently dysregulated in cancer. However, the mechanisms underlying impaired ferroptosis in oncogene-specific tumors remain poorly understood. Here we report a non- canonical role of lactate dehydrogenase B (LDHB), whose main activity is the conversion of lactate to pyruvate, in protecting KRAS-mutated lung cancer from ferroptosis. Silencing of LDHB impairs intracellular glutathione (GSH) metabolism and drives the hypersensitivity of KRAS-mutant cells to ferroptosis inducers by inhibiting the SLC7A11/GSH/GPX4 axis, a central antioxidant system against lipid peroxidation and ferroptosis by catalyzing GSH synthesis and utilization. Mechanistically, LDHB promotes SLC7A11 expression and GSH biosynthesis, and inhibition of LDHB confers metabolic synthetic lethality with ferroptosis inducers due to increased glutaminolysis and production of reactive oxygen species (ROS) in mitochondria, ultimately triggering ferroptosis of KRAS-driven lung cancer cells. Consequently, combined inhibition of LDHB and SLC7A11 synergistically suppresses tumor growth in multiple KRAS-mutant lung cancer implants and in an autochthonous model of Kras-induced lung adenocarcinoma. Taken together, our results reveal a hitherto unrecognized mechanism of ferroptosis defense by glycolytic LDHB and suggest a new strategy for the treatment of KRAS-dependent lung cancer.

cancer biology↗
bioRxiv2023

Changes in physicochemical properties and microbial community succession during leaf stacking fermentation

Leaf stacking fermentation involves enzymatic actions of many microorganisms and is an efficient and environmentally benign process for degrading macromolecular organic compounds. We investigated the dynamics of metabolite profiles, bacterial and fungal communities and their interactions during fermentation using cigar leaves from three geographic regions. The results showed that the contents of total sugar, reducing sugar, starch, cellulose, lignin, pectin, polyphenol and protein in cigar tobacco leaves was significantly decreased during fermentation. Notably, the furfural, neophytadiene, pyridine, benzyl alcohol, geranyl acetone, 2-butanone, 3-hydroxy-, N-hexanal, isoamylalcohol and 2,3-pentanedione were important features volatile aroma compounds during fermentation. The -diversity of fungi and bacteria initially increased and then decreased during fermentation. The microbial diversity was influenced by fermentation stages and growing locations, in which the fermentation stages had greater impacts on the microbial diversity than locations. Microbiome profiling had identified several core bacteria including Sphingomonas, Bacillus, Staphylococcus, Pseudomonas, Ralstonia, Massilia and Fibrobacter. Fungal biomarkers included Aspergillus, Penicillium, Fusarium, Cladosporium and Trichomonascus. Interestingly, the molecular ecological networks showed that the core taxa had significant correlations with metabolic enzymes and physicochemical properties; bacteria and fungi jointly participated in the carbohydrate and nitrogen compound degrading and volatile aroma compound chemosynthesis processes during fermentation. These studies provide insights into the coupling of material conversion and microbial community succession during leaf fermentation. IMPORTANCECigar tobacco leaves are still crude after air curing. Fermentation can eliminate the pungent and bitter taste of the leaves and promote the accumulations of aromatic compounds. Hitherto, there has been no systematic study on the material conversion, metabolic enzymes and microbial community changes and their interactions in fermented leaves. The significance of our research is in identifying the potential metabolic cooperation related to microbial community, which will greatly enhance our understanding of microorganism to convert macromolecular organic to small molecules during the leaf stacking fermentation process.

microbiology↗
bioRxiv2023

Bioengineering of a Lactococcus lactis subsp. lactis strain enhances nisin production and bioactivity.

Lactococcus lactis subsp. lactis is a food bacterium that has been utilized for decades in food fermentation and the development of high-value industrial goods. Among these, nisin is produced by several strains of L. lactis subsp. lactis plays a crucial role as a food bio-preservative. The relative expression of the gene cluster involved in nisin production was evaluated using qPCR analysis. Additionally, a series of re-transformations of the strain introducing multi copies of the nisA and nisRK genes involved in nisin biosynthesis were developed. The simultaneous expression of nisA and nisZ genes was used to potentiate the effective inhibition of foodborne pathogens. Further, qPCR analysis revealed a low expression of the nisA and nisRK genes in wild-type L. lactis subsp. lactis. After several re-transformations of the strain with the nisA and nisRK genes, a high expression of these genes was obtained, contributing to improved nisin production. Also, the co-expression of nisA and nisZ genes results in highly efficient antimicrobial activity. Hence, this study would supply an approach to enhancing nisin production during industrial processes and antimicrobial activity.

microbiology↗
bioRxiv2023

IL-17 activation undermines longevity and stress tolerance by inhibiting a protective transcriptional network

Aberrant cytokine secretion contributes to the pathogenesis of autoimmune diseases and age-related disorders, but the molecular mechanism underlying this is not entirely clear. Here, we elucidate how interleukin-17 (IL-17) overactivation shortens lifespan and damages defense mechanisms against stress in C. elegans. Our analysis reveals that NHR-49, the C. elegans ortholog of human PPAR and HNF4, is the central component in the transcriptional network undermined by increased IL-17 signaling. Both NHR-49 and its coactivator MDT-15 physically interact with the downstream components of IL-17 pathway, and their expression is significantly decreased when IL-17 signaling is enhanced. IL-17 overactivation also induces the expression and nucleus entry of the C. elegans ortholog of NF-{kappa}B inhibitor NFKI-1/I{kappa}B{zeta} to repress the activity of transcriptional coactivator MDT-15 and CBP-1. IL-17 signaling acts on neurons to modulate the activity of NFKI-1/I{kappa}B{zeta} and NHR-49. In addition, persistent IL-17 activation decreases the expression of HLH-30/TFEB, leading to the reduced transcription of lysosomal lipase genes in the distal tissues. All these jointly contribute to the increased sensitivity to oxidative stress of animals with enhanced IL-17 signaling. Collectively, our work illustrates a transcription system undermined by IL-17 overactivation in the animals without NF-{kappa}B, and provides mechanistic insight into the pathogenesis of abnormal IL-17 secretion.

cell biology↗
bioRxiv2023

Benchmark and optimization of AlphaFold structures based virtual screening strategy

Recent advancements in artificial intelligence such as AlphaFold, have enabled more accurate prediction of protein three-dimensional structure from amino acid sequences. This has attracted significant attention, especially for the application of AlphaFold in drug discovery. However, how to take full advantage of AlphaFold to assist with virtual screening remains elusive. We evaluate the AlphaFold structures of 51 selected targets from the DUD-E database in virtual screening. Our analyses show that the virtual screening performance of about 35% of the AlphaFold structures is equivalent to that of DUD-E structures, and about 25% of the AlphaFold structures yield better results than the DUD-E structures. Remarkably, AlphaFold structures produce slightly better results than the Apo structures. Moreover, we develop a new consensus scoring method based on Z-score standardization and exponential function, which shows improved screening performance compared to traditional scoring methods. By implementing a multi-stage virtual screening process and the new consensus scoring method, we are able to improve the speed of virtual screening by about nine times without compromising the enrichment factor. Overall, our results provide insights into the potential use of AlphaFold in drug discovery and highlight the value of consensus scoring and multi-stage virtual screening.

bioinformatics↗
bioRxiv2022

Microbiome features differentiating unsupervised-stratification based clusters of patients with abnormal glycometabolism

The alteration of gut microbiota structure plays a pivotal role in the pathogenesis of abnormal glycometabolism. However, the microbiome features identified in patient groups stratified solely based on glucose levels remain controversial among different studies.. In this study, we stratified 258 participants (discovery cohort) into three clusters according to an unsupervised method based on 16 clinical parameters involving the levels of blood glucose, insulin, and lipid. We found 67 cluster-specific microbiome features (i.e., amplicon sequence variants, ASVs) based on 16S rRNA gene V3-V4 region sequencing. Specifically, ASVs belonging to Barnesville and Alistipes were enriched in Cluster 1, in which participants had the lowest blood glucose levels, high insulin sensitivity, and high-fecal short-chain fatty acid concentration. ASVs belonging to Prevotella copri and Ruminococcus gnavus were enriched in Cluster 2, which was characterized by a moderate level of blood glucose, serious insulin resistance, and high levels of cholesterol and triglyceride. Cluster 3 was characterized by a high level of blood glucose and insulin deficiency, enriched with ASVs in P. copri and Bacteroides vulgatus. In addition, machine learning classifiers using the 67 cluster-specific ASVs were used to distinguish individuals in one cluster from those in the other two clusters both in discovery and testing cohorts (N = 83). Therefore, microbiome features identified based on the unsupervised stratification of patients with more inclusive clinical parameters may better reflect microbiota alterations associated with the progression of abnormal glycometabolism. IMPORTANCEThe gut microbiota is altered in patients with type 2 diabetes (T2D) and prediabetes. The association of particular bacteria with T2D, however, varied among studies, which has made it challenging to develop precision medicine approaches for the prevention and alleviation of T2D. Blood glucose level is the only parameter in clustering patients when identifying the T2D-related bacteria in previous studies. This stratification ignores the fact that patients within the same blood glucose range differ in their insulin resistance and dyslipidemia, which also may be related to disordered gut microbiota. In addition to parameters of blood glucose levels, we also used additional parameters involving insulin and lipid levels to stratify participants into three clusters and further identified cluster-specific microbiome features. We further validated the association between these microbiome features and glycometabolism with an independent cohort. This work highlights the importance of stratification of patients with blood glucose, insulin, and lipid levels when identifying the microbiome features associated with the progression of abnormal glycometabolism.

microbiology↗
bioRxiv2022

metaDMG - A Fast and Accurate Ancient DNA Damage Toolkit for Metagenomic Data

O_LIMotivation Under favourable conditions DNA molecules can persist for hundreds of thousands of years. Such genetic remains make up invaluable resources to study past assemblages, populations, and even the evolution of species. However, DNA is subject to degradation, and hence over time decrease to ultra low concentrations which makes it highly prone to contamination by modern sources. Strict precautions are therefore necessary to ensure that DNA from modern sources does not appear in the final data is authenticated as ancient. The most generally accepted and widely applied authenticity for ancient DNA studies is to test for elevated deaminated cytosine residues towards the termini of the molecules: DNA damage. To date, this has primarily been used for single organisms and recently for read assemblies, however, these methods are not applicable for estimating DNA damage for ancient metagenomes with tens and even hundreds of thousands of species. C_LIO_LIMethods We present metaDMG, a novel framework and toolkit that allows for the estimation, quantification and visualization of postmortem damage for single reads, single genomes and even metagenomic environmental DNA by utilizing the taxonomic branching structure. It bypasses any need for initial classification, splitting reads by individual organisms, and realignment. We have implemented a Bayesian approach that combines a modified geometric damage profile with a beta-binomial model to fit the entire model to the individual misincorporations at all taxonomic levels. C_LIO_LIResults We evaluated the performance using both simulated and published environmental DNA datasets and compared to existing methods when relevant. We find metaDMG to be an order of magnitude faster than previous methods and more accurate - even for complex metagenomes. Our simulations show that metaDMG can estimate DNA damage at taxonomic levels down to 100 reads, that the estimated uncertainties decrease with increased number of reads and that the estimates are more significant with increased number of C to T misincorporations. C_LIO_LIConclusion metaDMG is a state-of-the-art program for aDNA damage estimation and allows for the computation of nucleotide misincorporation, GC-content, and DNA fragmentation for both simple and complex ancient genomic datasets, making it a complete package for ancient DNA damage authentication. C_LI

bioinformatics↗
bioRxiv2022

PTPN1 deficiency modulates BMPR2 signaling and induces endothelial dysfunction in Pulmonary Arterial Hypertension

Bone morphogenic protein receptor 2 (BMPR2) expression and signaling are impaired in pulmonary arterial hypertension (PAH). How BMPR2 signaling is decreased in PAH is poorly understood. Protein tyrosine phosphatases (PTPs) play important roles in vascular remodeling in PAH. To identify whether PTPs modify BMPR2 signaling we used a siRNA-mediated high throughput screening of 22,124 murine genes in mouse myoblastoma reporter cells using ID1 expression as read-out for BMPR2 signaling. We further experimentally validated the top hit, PTPN1 (PTP1B), in human healthy pulmonary arterial endothelial cells (PAECs) either silenced by siRNA or exposed to hypoxia and confirmed its relevance to PAH by measuring PTPN1 levels in blood and PAECs collected from PAH patients. We identified PTPN1 as a novel regulator of BMPR2 signaling in PAECs, which is downregulated in the blood of PAH patients and documented that downregulation of PTPN1 is linked to endothelial dysfunction in PAECs. These findings point to a potential involvement for PTPN1 in PAH and will aid in our understanding of the molecular mechanisms involved in the disease.

cell biology↗
bioRxiv2022

Convergence and molecular evolution of floral fragrance after independent transitions to self fertilization

The study of the independent evolution of similar characters can highlight important ecological and genetic factors that drive phenotypic evolution. The transition from reproduction by outcrossing to self-fertilization has occurred frequently throughout plant evolution. A common trend in this transition is the reduction of flower features in the selfing lineages, including display size, flower signals and pollinators rewards. These changes are believed to evolve because resources invested in building attractive flowers are reallocated to other fitness functions as the pressures to attract pollinators decrease. We investigated the similarities in the evolution of flower fragrance after independent transitions to self-fertilization in Capsella. We identified a large number of compounds that are similarly changed in different selfer lineages, such that the composition of the flower scent can predict the mating system in this genus. We further demonstrate that the emission of some of these compounds convergently evolved based on mutations in different genes. In one of the Capsella selfing lineages, the loss of {beta}-ocimene emission was caused by a mutation altering subcellular localization of the ortholog of TERPENE SYNTHASE 2 without apparent effects on its biosynthetic activity. This mutation appears to have been selected at the early stage of this selfing lineage establishment through the capture of a variant segregating in the ancestral outcrossing population. The large extent of convergence in the independent evolution of flower scent, together with the evolutionary history and molecular consequences of a causal mutation, suggest that the emission of specific volatiles has important fitness consequences in self-fertilizing plants without obvious energetic benefits.

plant biology↗
bioRxiv2022

Whole-mount smFISH allows combining RNA and protein quantification at cellular and subcellular resolution

Multicellular organisms result from complex developmental processes largely orchestrated through the quantitative spatiotemporal regulation of gene expression. Yet, obtaining absolute counts of mRNAs at a 3-dimensional resolution remains challenging, especially in plants, due to high levels of tissue autofluorescence that prevent the detection of diffraction-limited fluorescent spots. In situ hybridization methods based on amplification cycles have recently emerged, but they are laborious and often lead to quantification biases. In this article, we present a simple method based on single molecule RNA fluorescence in situ hybridization (smFISH) to visualize and count the number of mRNA molecules in several intact plant tissues. In addition, with the use of fluorescent protein reporters, our method also enables simultaneous detection of mRNA and protein quantity, as well as subcellular distribution, in single cells. With this method, research in plants can now fully explore the benefits of the quantitative analysis of transcription and protein levels at cellular and subcellular resolution in plant tissues.

cell biology↗
bioRxiv2022

Global mosquito virome profiling and mosquito spatial diffusion pathways revealed by marker-viruses

Mosquitoes are vectors of numerous emergence and reemergence of mosquito-borne diseases, leading to an overwhelming global challenge. The boom in metagenomic studies promoted the increase of mosquito viruses being described, and studies from different regions of the world showed that mosquitoes harbor abundant and diverse viromes. However, there is still a lack of large-scale systematic comparison of viromes among various ecological factors such as the mosquito species/genera, location, etc, and consistent patterns associated with these factors are not clear. Here, we provide an overview of virome profiling that integrated the perspective of mosquito genus, locations, and climates based on the global scale, and redefined the core-virome. Our results also further implicate some mosquito-associated viruses strongly associated with the ecological factors and highlighted the evidence of mosquitoes cross-regional movements by the candidate marker viruses. The study may be helpful in gaining new insights into strategies to prevent arbovirus epidemics.

microbiology↗
bioRxiv2022

The Selection Landscape and Genetic Legacy of Ancient Eurasians

The Holocene (beginning [~]12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical, and mental health of present-day populations. Using a dataset of >1600 imputed ancient genomes 1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify major selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported, and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in >400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic, and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, while risk alleles for diabetes and Alzheimers disease are enriched for Western Hunter-gatherer ancestry. Our results suggest that ancient selection and migration were major contributors to the distribution of phenotypic diversity in present-day Europeans.

evolutionary biology↗
bioRxiv2022

Guild-level microbiome signature associated with COVID-19 severity and prognosis

COVID-19 severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples collected from 300 in-hospital COVID-19 patients at time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), Redundancy Analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Random Forest model based on these 33 HQMAGs classified patients from different severity groups (average AUC = 0.79). Co-abundance network analysis found that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Random Forest regression showed that these 33 HQMAGs at admission had the capacity to predict 8 clinical parameters, which are predictors for COVID-19 prognosis, at Day 7 in hospital. Moreover, the dominance of Guild 1 over Guild 2 at admission predicted the death/discharge outcome of the critical patients (AUC = 0.92). Random Forest models based on these 33 HQMAGs classified patients with different COVID-19 symptom severity, and differentiated COVID-19 patients from healthy subjects, non-COVID-19, and pneumonia controls in three independent datasets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission.

microbiology↗
bioRxiv2022

Imprinted SARS-CoV-2 humoral immunity induces converging Omicron RBD evolution

Continuous evolution of Omicron has led to a rapid and simultaneous emergence of numerous variants that display growth advantages over BA. 5. Despite their divergent evolutionary courses, mutations on their receptor-binding domain (RBD) converge on several hotspots. The driving force and destination of such convergent evolution and its impact on humoral immunity remain unclear. Here, we demonstrate that these convergent mutations can cause striking evasion of neutralizing antibody (NAb) drugs and convalescent plasma, including those from BA.5 breakthrough infection, while maintaining sufficient ACE2 binding capability. BQ.1.1.10, BA.4.6.3, XBB, and CH. 1.1 are the most antibody-evasive strain tested, even exceeding SARS-CoV-1 level. To delineate the origin of the convergent evolution, we determined the escape mutation profiles and neutralization activity of monoclonal antibodies (mAbs) isolated from BA.2 and BA.5 breakthrough-infection convalescents. Importantly, due to humoral immune imprinting, BA.2 and especially BA.5 breakthrough infection caused significant reductions in the epitope diversity of NAbs and increased proportion of non-neutralizing mAbs, which in turn concentrated humoral immune pressure and promoted convergent evolution. Moreover, we showed that the convergent RBD mutations could be accurately inferred by integrated deep mutational scanning (DMS) profiles, and the evolution trends of BA.2.75/BA.5 subvariants could be well-simulated through constructed convergent pseudovirus mutants. Together, our results suggest current herd immunity and BA.5 vaccine boosters may not provide good protection against infection. Broad-spectrum SARS-CoV-2 vaccines and NAb drugs development should be highly prioritized, and the constructed mutants could help to examine their effectiveness in advance.

immunology↗
bioRxiv2022

Sex differences in inter-individual gene expression variability across human tissues

Understanding phenotypic sex differences has long been a goal of biology from both a medical and evolutionary perspective. Although much attention has been paid to mean differences in phenotype between the sexes, little is known about sex differences in phenotypic variability. To gain insight into sex differences in inter-individual variability at the molecular level, we analyzed RNA-seq data from 43 tissues from the Genotype-Tissue Expression project (GTEx). Within each tissue, we identified genes that show sex differences in gene expression variability. We found that these sex-differentially variable (SDV) genes are associated with various important biological functions, including sex hormone response, immune response, and other signaling pathways. By analyzing single-cell RNA sequencing data collected from breast epithelial cells, we found that genes with sex differences in gene expression variability in breast tissue tend to be expressed in a cell-type-specific manner. We looked for an association between SDV expression and Graves disease, a well-known heavily female-biased disease, and found a significant enrichment of Graves associated genes among genes with higher variability in females in thyroid tissue. This suggests a possible role for SDV expression in the context of sex-biased disease. We then examined the evolutionary constraints acting on genes with sex differences in variability and found that they exhibit evidence of increased selective constraint. Through analysis of sex-biased eQTL data, we found evidence that SDV expression may have a genetic basis. Finally, we propose a simple evolutionary model for the emergence of sex-differentially variable expression from sex-specific constraints.

evolutionary biology↗
bioRxiv2022

MHA, an interactive website for scRNA-seq data of male genitourinary development and disease

The development of single-cell sequencing technology has expanded the understanding of cell heterogeneity and disease progression in the male genitourinary system. However, complex processing processes and unprofessional analytical annotations limit the daily use and wildly sharing of published datasets. Here, we describe the Male Health Atlas (MHA), an easy-to-operate online visual website focused on the male genitourinary system, allowing researchers to quickly search for expression patterns of one or multiple genes, and dynamic changes of gene expression during tissue development or under pathological states. At present, the MHA includes nine objects, two species, five types of male genitourinary tissues/organs, and 258,777 single-cell profiles. Compared with other single-cell databases, the MHA has the following advantages: (1) It is easy to operate, and users can complete retrieval and output of results within 5 min without any bioinformatics skills; (2) The selection and analysis of data are under professional supervision of researchers in the male genitourinary field; (3) It contains most of the main male-specific organs and will continue to be updated; (4) MHA provides multi-dimensional output patterns, including tSNE/UMAP, violin, and bubble plot output for displaying single or multiple genes. MHA is the first single-cell database website in the field of andrology and male reproduction, providing researchers with scRNA-seq resources and an accessible tool. MHA is freely available at http://malehealthatlas.cn/.

molecular biology↗
bioRxiv2022

Genital tract microbiome dynamics are associated with time of Chlamydia infection

BackgroundWe have previously shown that the time of Chlamydia infection was crucial in determining the chlamydial infectivity and pathogenesis. This study aims to determine whether the time of Chlamydia infection affects the genital tract microbiome. This study analyzed mice vaginal, uterine, and ovary/oviduct microbiome with and without Chlamydia infection. The mice were infected with Chlamydia at either 10:00 am (ZT3) or 10:00 pm (ZT15). ResultsThe results showed that mice infected at ZT3 had higher Chlamydia infectivity than those infected at ZT15. There was more variation in the compositional complexity of the vaginal microbiome (alpha diversity) of mice infected at ZT3 than those mice infected at ZT15 throughout the infection within each treatment group, with both Shannon and Simpson diversity index values decreased over time. The analysis of samples collected four weeks post-infection showed that there were significant taxonomical differences (beta diversity) between different parts of the genital tract--vagina, uterus, and ovary/oviduct--and this difference was associated with the time of infection. Firmicutes and Proteobacteria were the most abundant phyla within the microbiome in all three genital tract regions for all the samples collected during this experiment. Additionally, Firmicutes was the dominant phylum in the uterine microbiome of ZT3 Chlamydia infected mice. ConclusionThe results show that the time of infection is associated with the microbial dynamics in the genital tract. And this association is more robust in the upper genital tract than in the vagina. This result implies that more emphasis should be placed on understanding the changes in the microbial dynamics of the upper genital tract over the course of infection.

microbiology↗