Biology subjects

Ehrlich, G. D.

Publications and source records attributed to Ehrlich, G. D..

9 recordsLinked to original sources

bioRxiv2026

Identification of disease-specific alleles and gene duplications from 1,600 Haemophilus influenzae genomes using predicted protein analyses from an unsupervised language model and clinical metadata

Haemophilus influenzae, a Gram-negative bacterium that is an obligate commensal of the human nasopharynx, is associated with both acute and chronic infections of the ears, adenoids, sinuses, and lungs, as well as pelvic inflammatory disease, sepsis, and meningitis. This diverse array of clinical disease phenotypes is due to H. influenzaes natural competence providing for frequent distributed gene exchange among strains during polyclonal colonizations. We performed whole genome sequencing (WGS) on [~]1000 H. influenzae strains and combined these data with [~]600 publicly available genomes. Clinical metadata including isolation site and disease were available for all strains. Our goal was to identify variations in protein sequences inferred from the WGS that correlate with the clinical metadata. We employed the alpha-fold unsupervised machine-learning model to all protein sequences. For each unique AA sequence, a numerical vector was generated reflecting the proteins biochemical properties. Multidimensional clustering was used to group variants into clusters by distance. For gene groups with two or more clusters, clinical metadata from the strain of origin was overlayed and subsequently tested for correlation with the clustering. This allowed identification of multiple gene groups with clusters of variants that correlated significantly with the patients disease. COG category analysis showed that many of the significant gene groups were associated with antibiotic targets. The TbpA gene group type was found to be significantly correlated with disease type with three of five variant clusters having a 95% prevalence among strains that were isolated from the lungs of COPD patients or other lower pulmonary tract infections.

genomics↗

bioRxiv2025

Development of a long-read high-throughput chromatin conformation capture method for evaluating both cis and trans interactions between integrated Hepatitis B Virus and host genomes.

High-throughput chromatin conformation capture (Hi-C) has been utilized for characterizing the 3-dimensional (3D) interactome of the genome. However, short-read sequencing approaches have limited the information it provides, especially for integrated proviral DNAs . Herein we describe the development of a pipeline to investigate the 3D interactome associated with integrated Hepatitis B Virus (HBV) DNAs (iDNAs) to further understand the role of HBV iDNA in liver carcinogenesis. We employed long-read DNA sequencing combined with a novel target-pull-down library construction approach that protects against DNA shearage resulting in greatly improved sensitivity and specificity for the targeted HBV iDNA. Most importantly, we successfully increased the length of captured Hi-C library to the multi-kilobase-level and report Hi-C contacts based on a custom-developed informatics pipeline. We anticipate this combined laboratory{-}informatics pipeline will provide a more comprehensive view of HBV iDNA-host genomic interactions associated with their role in liver carcinogenesis, but even more importantly that it should be generalizable for the study of the geno-topological effects associated with any type of integrated DNA. (word count: 164/250)

genomics↗

bioRxiv2025

Outer membrane vesicles from Bacteroides fragilis contain coding and non-coding small RNA species that modulate inflammatory signaling in intestinal epithelial cells.

Alterations to the community structure and function of the microbiome are associated with changes to host physiology, including immune responses. However, the contribution of microbe-derived RNAs carried by outer membrane vesicles (OMVs) to host immune responses remain unclear. This study investigated the role of OMVs and OMV-associated small RNA (sRNA) species from pathogenic and commensal Bacteroides fragilis (ETBF and NTBF respectively) in eliciting different immune responses from intestinal epithelial cells. To distinguish the differences in the sRNA profiles of the two strains and their OMVs, RNA-seq, qRT-PCR, and northern blotting were conducted to identify enrichment of discrete sRNA species in OMVs, which were also differentially expressed between the two strains. Specifically, both coding and non-coding RNAs were enriched in OMVs from NTBF and ETBF, with BF9343_RS22680 and BF9343_RS17870 being significantly enriched in ETBF OMVs compared to NTBF. To understand the effects of OMVs on pattern recognition receptors, reporter cells of Toll-like receptor (TLR) activation were treated with OMVs, demonstrating activation of TLRs 2, 3, and 7. Treatment of Caco-2 and HT29-MTX cells with OMVs demonstrated increased expression of IL-8. Surprisingly, we discovered that degradation of RNase-accessible RNAs within ETBF OMVs, but not NTBF OMVs, resulted in vesicles with enhanced capacity to stimulate IL-8 expression, indicating that these extravesicular RNAs exert an immunosuppressive effect. This suggests a dual role for OMV-associated RNAs in modulating host immune responses, with implications for both bacterial pathogenesis and therapeutic applications. Graphical Abstract

molecular biology↗

bioRxiv2022

Evidence for the Existence of a Bacterial Etiology for Alzheimers Disease and for a Temporal-Spatial Development of a Pathogenic Microbiome in the Brain

BackgroundOver the last few decades, a growing body of evidence suggests a role for various infectious agents in Alzheimers Disease (AD) pathogenesis. Despite diverse pathogens (virus, bacteria, or fungi) being detected in AD subjects brains, most research has focused on individual pathogens and only a few studies investigated the hypothesis of a bacterial brain microbiome. We profiled the bacterial communities present in non-demented controls and AD subjects brains. ResultsWe obtained post-mortem samples from the brains of 32 individual subjects, comprising 16 AD and 16 control aged-matched subjects with a total of 130 samples from the frontal and temporal lobes and entorhinal cortex. We used full-length 16S rRNA gene amplification with Pacific Biosciences sequencing technology to identify the bacteria. We detected bacteria in the brains of both cohorts with the principal bacteria comprising Propionibacterium acnes (recently renamed Cutibacterium acnes) and two species each of Acinetobacter and Comamonas genera. We used a hierarchical Bayesian method to detect differences in relative abundance among AD and control groups. Because of large abundance variances we also employed an unconventional analysis approach that utilized Latent Dirichlet Allocation, often used in computational linguistics. This allowed us to identify 5 classes of samples, each revealing a different microbiome. Assuming that samples represented infections that potentially began at different times, we ordered these classes in time, finding that the last class exclusively explained the existence or non-existence of AD. ConclusionsThe AD-related pathogenicity of the brain microbiome seems to be based on a complex polymicrobial dynamic. The time ordering revealed a rise and fall of the abundance of Propionibacterium acnes with pathogenicity occurring for an off-peak abundance level in association with at least one other bacterium from a set of genera that included: Methylobacterium, Bacillus, Caulobacter, Delftia, and Variovorax. P. acnes may also be involved with outcompeting the Comamonas species, which were strongly associated with non-demented brain microbiome, whose early destruction could be the first stage of the disease. The statistical results are also consistent with a leaky blood brain barrier or lymphatic network that allows bacteria, viruses, fungi, or other pathogens to enter the brain.

microbiology↗

bioRxiv2020

The Development of a Pipeline for the Identification and Validation of Small-Molecule RelA Inhibitors for Use as Anti-biofilm Drugs

Biofilm infections have no effective medical treatments and can only be disrupted via physical means. This means that any biofilm infection that is not addressable surgically can never be eliminated and can only be managed as a chronic disease. Therefore, there is an urgent need for the development of new classes of drugs that can target the metabolic mechanisms within biofilms which render them recalcitrant to traditional antibiotics. This antibiotic recalcitrance of bacterial biofilms can be attributed largely to the formation of persister cells within the biofilm structure. These biofilm persister cells can be resistant to up to 1000 times the minimal inhibitory concentrations of many antibiotics as compared to their planktonic envirovars; they are thought to be the prokaryotic equivalent of metazoan stem cells. Their metabolic resistance has been demonstrated to be an active process induced by the stringent response that is triggered by the ribosomally-associated enzyme RelA in response to amino acid starvation. This 84-kD pyrophosphokinase produces the "magic spot" alarmones, collectively called (p)ppGpp. These alarmones act by directly regulating transcription by binding to RNA polymerase. These transcriptional changes lead to a major shift in cellular function to both upregulate oxidative stress-combating enzymes and down regulate major cellular functions associated with growth and replication. These changes in gene expression produce the quiescent persister cells. In this work, we describe a hybrid in silico-laboratory pipeline for identifying and validating small-molecule inhibitors of RelA for use in the combinatorial treatment of bacterial biofilms as re-potentiators of classical antibiotics.

microbiology↗

bioRxiv2019

Genome-wide analysis of DNA uptake by naturally competent Haemophilus influenzae

The genomes of naturally competent Pasteurellaceae and Neisseriaceae have many short uptake sequences (USS), which allow them to distinguish self-DNA from foreign DNA. To fully characterize this preference we developed genome-wide maps of DNA uptake using both a sequence-based computational model and genomic DNA that had been sequenced after uptake by and recovery from competent Haemophilus influenzae cells. When DNA fragments were shorter than the average USS spacing of ~1000 bp, sharp peaks of uptake were centered at USS and separated by valleys with 1000-fold lower uptake. Long DNA fragments (1.5-17 kb) gave much less variation, with 90% of positions having uptake within two-fold of the mean. All detectable uptake biases arose from sequences that fit the USS uptake motif. Simulated competition predicted that, in its respiratory tract environment, H. influenzae will efficiently take up its own DNA even when human DNA is present in 100-fold excess.

microbiology↗

bioRxiv2019

Complete genome sequence of Escherichia coli C - an old model organism with a new application in biofilm research

Escherichia coli C forms more robust biofilms than the other laboratory strains. Biofilm formation and cell aggregation under a high shear force depends on temperature and salt concentrations. It is the last of five E. coli strains (C, K12, B, W, Crooks) designated as safe for laboratory purposes whose genome has not been sequenced. Here we present the complete genomic sequence of this strain in which we utilized both long-read PacBio-based sequencing and high resolution optical mapping to confirm a large inversion in comparison to the other laboratory strains. Notably, DNA sequence comparison revealed the absence of several genes thought to be involved in biofilm formation, including antigen 43, waaSBOJYZUL for LPS synthesis, and cpsB for curli synthesis. The first main difference we identified that likely affects biofilm formation is the presence of an IS3-like insertion sequence in front of the carbon storage regulator csrA gene. This insertion is located 86 bp upstream of the csrA start codon inside the -35 region of P4 promoter and blocks the transcription from the sigma32 and sigma70 promoters P1-P3 located further upstream. The second is the presence of an IS5/IS1182 in front of the csgD gene, which may drive its overexpression in biofilm. And finally, E. coli C encodes an additional sigma70 subunit overexpressed in biofilm and driven by the same IS3-like insertion sequence. Promoter analyses using GFP gene fusions and total expression profiles using RNA-seq analyses comparing planktonic and biofilm envirovars provided insights into understanding this regulatory pathway in E. coli. IMPORTANCEBiofilms are crucial for bacterial survival, adaptation, and dissemination in natural, industrial, and medical environments. Most laboratory strains of E. coli grown for decades in vitro have evolved and lost their ability to form biofilm, while environmental isolates that can cause infections and diseases are not safe to work with. Here, we show that the historic laboratory strain of E. coli C produces a robust biofilm and can be used as a model organism for multicellular bacterial research. Furthermore, we ascertained the full genomic sequence as well as gene expression profiles of both the biofilm and planktonic envirovars of this classic strain, which provide for a base level of characterization and make it useful for many biofilm-based applications.

microbiology↗

bioRxiv2018

Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes

BackgroundPan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family- or genus-level taxonomy. Moreover, sequencing errors often inflate the number of taxa present. Pacific Biosciences (PacBios) long-read technology in particular suffers from high error rates per base. Herein we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome data\n\nResultsAnalysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity. Examination of a 250-plus species mock community demonstrated correct species-level classification of >90% of taxa and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed. Propiniobacterium acnes (recently renamed Cutibacterium acnes [1]) was the predominant species throughout, but was found at distinct relative abundances by site.\n\nConclusionsOur microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt) overcomes deficits of standard marker gene based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution. Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.

bioinformatics↗

bioRxiv2018

Microbiome-TP53 Gene Interaction in Human Lung Cancer

BackgroundLung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesized that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from controls (n=33) and cancer cases (n=143), we conducted 16S rRNA bacterial gene sequencing, with RNA-seq data from lung cancer cases in The Cancer Genome Atlas (n=1112) serving as the validation cohort.\n\nResultsOverall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma (SCC) specifically, a separate group of taxa were identified, in which Acidovorax was enriched in smokers (P =0.0013). Acidovorax temporans was identified by fluorescent in situ hybridization within tumor sections, and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax, exhibited higher abundance among the subset of SCC cases with TP53 mutations, an association not seen in adenocarcinomas (AD).\n\nConclusionsThe results of this comprehensive study show both a microbiome-gene and microbiome-exposure interactions in SCC lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can damage epithelial function, have a unique bacterial consortia which is higher in relative abundance in smoking-associated SCC. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection.

cancer biology↗