Education & Certifications
Doctor of Philosophy, University of Connecticut, Genetics (2016)
Bachelor of Technology, Dr. M.G.R Educational and Research Institute, Industrial Biotechnology (2007)
Re-visiting humoral constitutive antibacterial heterogeneity in bloodstream infections.
The Lancet. Infectious diseases
Although cellular immunity has garnered much attention in the era of single-cell technologies, humoral innate immunity has receded in priority due to its presumed limited roles. Hence, despite the long-recognised bactericidal activity of serum-a functional characteristic of constitutive humoral immunity-much remains unclear regarding mechanisms underlying its inter-individual heterogeneity and clinical implications in bloodstream infections. Recent work suggests that the immediate antimicrobial effect of humoral innate immunity contributes to suppression of the excessive inflammatory responses to infection by reducing the amount of pathogen-associated molecular patterns. In this Personal View, we propose the need to re-explore factors underlying the inter-individual heterogeneity in serum antibacterial competence as a new approach to better understand humoral innate immunity and revisit the clinical use of measuring serum antibacterial activity in the management of bacterial bloodstream infections. Given the current emphasis on subtyping sepsis, a serum bactericidal assay might prove useful in defining a distinct sepsis endotype, to enable more personalised management.
View details for DOI 10.1016/S1473-3099(23)00494-2
View details for PubMedID 37944543
Neutrophil Extracellular Traps have DNAzyme activity that drives bactericidal potential.
bioRxiv : the preprint server for biology
The mechanisms of bacterial killing by neutrophil extracellular traps (NETs) are unclear. DNA, the largest component of NETs is believed to merely be a scaffold with minimal antimicrobial activity through the charge of the backbone. Here, we report that NETs DNA is beyond a scaffold and produces hydroxyl free radicals through the spatially concentrated G-quadruplex/hemin DNAzyme complexes, driving bactericidal effects. Immunofluorescence staining showed colocalization of G-quadruplex and hemin in extruded NETs DNA, and Amplex UltraRed assay portrayed its peroxidase activity. Proximity labeling of bacteria revealed localized concentration of radicals resulting from NETs bacterial trapping. Ex vivo bactericidal assays revealed that G-quadruplex/hemin DNAzyme is the primary driver of bactericidal activity in NETs. NETs are DNAzymes that may have important biological consequences.One-Sentence Summary: G-quadruplex/hemin DNAzymes may be major contributors to biological consequences of neutrophil extracellular traps.
View details for DOI 10.1101/2023.10.23.563618
View details for PubMedID 37961380
Phage diversity in cell-free DNA identifies bacterial pathogens in human sepsis cases.
Bacteriophages, viruses that infect bacteria, have great specificity for their bacterial hosts at the strain and species level. However, the relationship between the phageome and associated bacterial population dynamics is unclear. Here we generated a computational pipeline to identify sequences associated with bacteriophages and their bacterial hosts in cell-free DNA from plasma samples. Analysis of two independent cohorts, including a Stanford Cohort of 61 septic patients and 10 controls and the SeqStudy cohort of 224 septic patients and 167 controls, reveals a circulating phageome in the plasma of all sampled individuals. Moreover, infection is associated with overrepresentation of pathogen-specific phages, allowing for identification of bacterial pathogens. We find that information on phage diversity enables identification of the bacteria that produced these phages, including pathovariant strains of Escherichia coli. Phage sequences can likewise be used to distinguish between closely related bacterial species such as Staphylococcus aureus, a frequent pathogen, and coagulase-negative Staphylococcus, a frequent contaminant. Phage cell-free DNA may have utility in studying bacterial infections.
View details for DOI 10.1038/s41564-023-01406-x
View details for PubMedID 37308590
View details for PubMedCentralID 5594678
Rapid Molecular Phenotypic Antimicrobial Susceptibility Test for Neisseria gonorrhoeae Based on Propidium Monoazide Viability PCR.
ACS infectious diseases
Neisseria gonorrhoeae (NG) is an urgent threat to antimicrobial resistance (AMR) worldwide. NG has acquired rapid resistance to all previously recommended treatments, leaving ceftriaxone monotherapy as the first and last line of therapy for uncomplicated NG. The ability to rapidly determine susceptibility, which is currently nonexistent for NG, has been proposed as a strategy to preserve ceftriaxone by using alternative treatments. Herein, we used a DNA-intercalating dye in combination with NG-specific primers/probes to generate qPCR cycle threshold (Ct) values at different concentrations of 2 NG-relevant antimicrobials. Our proof-of-concept dual-antimicrobial logistic regression model based on the differential Ct measurements achieved an AUC of 0.93 with a categorical agreement for the susceptibility of 84.6%. When surveying the performance against each antimicrobial separately, the model predicted 90 and 75% susceptible and resistant strains, respectively, to ceftriaxone and 66.7 and 83.3% susceptible and resistant strains, respectively, to ciprofloxacin. We further validated the model against the individual replicates and determined the accuracy of the model in classifying susceptibility agnostic of the inoculum size. We demonstrated a novel PCR-based approach to determine phenotypic ciprofloxacin and ceftriaxone susceptibility information for NG with reasonable accuracy within 30 min, a significant improvement compared to the conventional method which could take multiple days.
View details for DOI 10.1021/acsinfecdis.3c00096
View details for PubMedID 37115656
Rapid molecular phenotypic antimicrobial susceptibility test for Neisseria gonorrhoeae based on propidium monoazide viability PCR.
bioRxiv : the preprint server for biology
Neisseria gonorrhoeae (NG) is an urgent threat to antimicrobial resistance (AMR) worldwide. NG has acquired rapid resistance to all previously recommended treatments leaving ceftriaxone monotherapy as the first and last line of therapy for uncomplicated NG. The ability to rapidly determine susceptibility, which is currently nonexistent for NG, has been proposed as a strategy to preserve ceftriaxone by using alternative treatments. Herein, we used a DNA-intercalating dye in combination with NG-specific primers/probes to generate qPCR cycle threshold (Ct) values at different concentrations of 2 NG-relevant antimicrobials. Our proof of concept dual-antimicrobial logistic regression model based on the differential Ct measurements achieved an AUC of 0.93 with a categorical agreement for susceptibility of 84.6%. When surveying the performance against each antimicrobial separately, the model predicted 90% and 75% susceptible and resistant strains respectively to ceftriaxone and 66.7% and 83.3% susceptible and resistant strains respectively to ciprofloxacin. We further validated the model against the individual replicates and determined the accuracy of the model in classifying susceptibility agnostic of the inoculum size. We demonstrated a novel PCR-based approach to determine phenotypic ciprofloxacin and ceftriaxone susceptibility information for NG with reasonable accuracy in under 30 min, a significant improvement compared to the conventional method which takes 3 days.Table of Content Graphic:
View details for DOI 10.1101/2023.03.01.530513
View details for PubMedID 36909582
Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department.
Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 "Low" severity classification and 7/60 (11.7%) in the "Moderate" severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients' risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources.
View details for DOI 10.1128/spectrum.02305-22
View details for PubMedID 36250865
Disease diagnostics using machine learning of immune receptors.
bioRxiv : the preprint server for biology
Clinical diagnoses rely on a wide variety of laboratory tests and imaging studies, interpreted alongside physical examination and documentation of symptoms and patient history. However, the tools of diagnosis make little use of the immune systemas internal record of specific disease exposures encoded by the antigen-specific receptors of memory B cells and T cells. We have combined extensive receptor sequence datasets with three different machine learning representations of the contents of immune repertoires to develop an interpretive framework, MAchine Learning for Immunological Diagnosis (Mal-ID) , that screens for multiple illnesses simultaneously. This approach can already reliably distinguish a wide range of disease states, including specific acute or chronic infections, and autoimmune or immunodeficiency disorders, and could contribute to identifying new infectious diseases as they emerge. Importantly, many features of the model of immune receptor sequences are human-interpretable. They independently recapitulate known biology of the responses to infection by SARS-CoV-2 or HIV, and reveal common features of autoreactive immune receptor repertoires, indicating that machine learning on immune repertoires can yield new immunological knowledge.
View details for DOI 10.1101/2022.04.26.489314
View details for PubMedID 35547855
Diagnosis of Bloodstream Infections: An Evolution of Technologies towards Accurate and Rapid Identification and Antibiotic Susceptibility Testing.
Antibiotics (Basel, Switzerland)
2022; 11 (4)
Bloodstream infections (BSI) are a leading cause of death worldwide. The lack of timely and reliable diagnostic practices is an ongoing issue for managing BSI. The current gold standard blood culture practice for pathogen identification and antibiotic susceptibility testing is time-consuming. Delayed diagnosis warrants the use of empirical antibiotics, which could lead to poor patient outcomes, and risks the development of antibiotic resistance. Hence, novel techniques that could offer accurate and timely diagnosis and susceptibility testing are urgently needed. This review focuses on BSI and highlights both the progress and shortcomings of its current diagnosis. We surveyed clinical workflows that employ recently approved technologies and showed that, while offering improved sensitivity and selectivity, these techniques are still unable to deliver a timely result. We then discuss a number of emerging technologies that have the potential to shorten the overall turnaround time of BSI diagnosis through direct testing from whole blood-while maintaining, if not improving-the current assay's sensitivity and pathogen coverage. We concluded by providing our assessment of potential future directions for accelerating BSI pathogen identification and the antibiotic susceptibility test. While engineering solutions have enabled faster assay turnaround, further progress is still needed to supplant blood culture practice and guide appropriate antibiotic administration for BSI patients.
View details for DOI 10.3390/antibiotics11040511
View details for PubMedID 35453262
Detection of bacterial co-infections and prediction of fatal outcomes in COVID-19 patients presenting to the emergency department using a 29 mRNA host response classifier.
medRxiv : the preprint server for health sciences
Objective: Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial co-infection, and determining illness severity since current practices require separate workflows. Here we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting SARS-CoV-2 infection, bacterial co-infections, and predicting clinical severity of COVID-19.Methods: 161 patients with PCR-confirmed COVID-19 (52.2% female, median age 50.0 years, 51% hospitalized, 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene Blood RNA) and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter.Results: The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrolment and the remaining oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial co-infection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e. Clostridioides difficile colitis (n=1), urinary tract infection (n=1), and clinically diagnosed bacterial infections (n=3) for a specificity of 99.4%. 2/101 (2.8%) patients in the IMX-SEV-3 Low and 7/60 (11.7%) in the Moderate severity classifications died within thirty days of enrollment.Conclusions: IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19, bacterial co-infections, and predicted patientsa risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management including more accurate treatment decisions and optimized resource utilization.
View details for DOI 10.1101/2022.03.14.22272394
View details for PubMedID 35313598
Association Between SARS-CoV-2 RNAemia and Postacute Sequelae of COVID-19.
Open forum infectious diseases
2022; 9 (2): ofab646
Determinants of Post-Acute Sequelae of COVID-19 are not known. Here we show that 83.3% of patients with viral RNA in blood (RNAemia) at presentation were symptomatic in the post-acute phase. RNAemia at presentation successfully predicted PASC, independent of patient demographics, worst disease severity, and length of symptoms.
View details for DOI 10.1093/ofid/ofab646
View details for PubMedID 35111870
View details for PubMedCentralID PMC8802799
- A Novel Platform Using RNA Signatures To Accelerate Antimicrobial Susceptibility Testing in Neisseria gonorrhoeae (vol 58, e01152-20, 2020) JOURNAL OF CLINICAL MICROBIOLOGY 2021; 59 (3)
- Erratum for Hashemi et al., "A Novel Platform Using RNA Signatures To Accelerate Antimicrobial Susceptibility Testing in Neisseria gonorrhoeae". Journal of clinical microbiology 2021; 59 (3)
SARS-CoV-2 RNAemia predicts clinical deterioration and extrapulmonary complications from COVID-19.
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
The determinants of COVID-19 disease severity and extrapulmonary complications (EPCs) are poorly understood. We characterized relationships between SARS-CoV-2 RNAemia and disease severity, clinical deterioration, and specific EPCs.We used quantitative (qPCR) and digital (dPCR) PCR to quantify SARS-CoV-2 RNA from plasma in 191 patients presenting to the Emergency Department (ED) with COVID-19. We recorded patient symptoms, laboratory markers, and clinical outcomes, with a focus on oxygen requirements over time. We collected longitudinal plasma samples from a subset of patients. We characterized the role of RNAemia in predicting clinical severity and EPCs using elastic net regression.23.0% (44/191) of SARS-CoV-2 positive patients had viral RNA detected in plasma by dPCR, compared to 1.4% (2/147) by qPCR. Most patients with serial measurements had undetectable RNAemia within 10 days of symptom onset, reached maximum clinical severity within 16 days, and symptom resolution within 33 days. Initially RNAaemic patients were more likely to manifest severe disease (OR 6.72 [95% CI, 2.45 - 19.79]), worsening of disease severity (OR 2.43 [95% CI, 1.07 - 5.38]), and EPCs (OR 2.81 [95% CI, 1.26 - 6.36]). RNA load correlated with maximum severity (r = 0.47 [95% CI, 0.20 - 0.67]).dPCR is more sensitive than qPCR for the detection of SARS-CoV-2 RNAemia, which is a robust predictor of eventual COVID-19 severity and oxygen requirements, as well as EPCs. Since many COVID-19 therapies are initiated on the basis of oxygen requirements, RNAemia on presentation might serve to direct early initiation of appropriate therapies for the patients most likely to deteriorate.
View details for DOI 10.1093/cid/ciab394
View details for PubMedID 33949665
Profiling chromatin accessibility responses in human neutrophils with sensitive pathogen detection.
Life science alliance
2021; 4 (8)
Sepsis, sequela of bloodstream infections and dysregulated host responses, is a leading cause of death globally. Neutrophils tightly regulate responses to pathogens to prevent organ damage. Profiling early host epigenetic responses in neutrophils may aid in disease recognition. We performed assay for transposase-accessible chromatin (ATAC)-seq of human neutrophils challenged with six toll-like receptor ligands and two organisms; and RNA-seq after Escherichia coli exposure for 1 and 4 h along with ATAC-seq. ATAC-seq of neutrophils facilitates detection of pathogen DNA. In addition, despite similarities in genomic distribution of differential chromatin changes across challenges, only a fraction overlaps between the challenges. Ligands depict shared signatures, but majority are unique in position, function, and challenge. Epigenomic changes are plastic, only ∼120 are shared by Ecoli challenges over time, resulting in varied differential genes and associated processes. We identify three classes of gene regulation, chromatin access changes in the promoter; changes in the promoter and distal enhancers; and controlling expression through changes solely in distal enhancers. These and transcription factor footprinting reveal timely and challenge specific mechanisms of transcriptional regulation in neutrophils.
View details for DOI 10.26508/lsa.202000976
View details for PubMedID 34145026
Insights into gene expression changes under conditions that facilitate horizontal gene transfer (mating) of a model archaeon.
2020; 10 (1): 22297
Horizontal gene transfer is a means by which bacteria, archaea, and eukaryotes are able to trade DNA within and between species. While there are a variety of mechanisms through which this genetic exchange can take place, one means prevalent in the archaeon Haloferax volcanii involves the transient formation of cytoplasmic bridges between cells and is referred to as mating. This process can result in the exchange of very large fragments of DNA between the participating cells. Genes governing the process of mating, including triggers to initiate mating, mechanisms of cell fusion, and DNA exchange, have yet to be characterized. We used a transcriptomic approach to gain a more detailed knowledge of how mating might transpire. By examining the differential expression of genes expressed in cells harvested from mating conditions on a filter over time and comparing them to those expressed in a shaking culture, we were able to identify genes and pathways potentially associated with mating. These analyses provide new insights into both the mechanisms and barriers of mating in Hfx. volcanii.
View details for DOI 10.1038/s41598-020-79296-w
View details for PubMedID 33339886
Comparative Metatranscriptomics of Periodontitis Supports a Common Polymicrobial Shift in Metabolic Function and Identifies Novel Putative Disease-Associated ncRNAs.
Frontiers in microbiology
2020; 11: 482
Periodontitis is an inflammatory disease that deteriorates bone supporting teeth afflicting ∼743 million people worldwide. Bacterial communities associated with disease have been classified into red, orange, purple, blue, green, and yellow complexes based on their roles in the periodontal pocket. Previous metagenomic and metatranscriptomics analyses suggest a common shift in metabolic signatures in disease vs. healthy communities with up-regulated processes including pyruvate fermentation, histidine degradation, amino acid metabolism, TonB-dependent receptors. In this work, we examine existing metatranscriptome datasets to identify the commonly differentially expressed transcripts and potential underlying RNA regulatory mechanisms behind the metabolic shifts. Raw RNA-seq reads from three studies (including 49 healthy and 48 periodontitis samples) were assembled into transcripts de novo. Analyses revealed 859 differentially expressed (DE) transcripts, 675 more- and 174 less-expressed. Only ∼20% of the DE transcripts originate from the pathogenic red/orange complexes, and ∼50% originate from organisms unaffiliated with a complex. Comparison of expression profiles revealed variations among disease samples; while specific metabolic processes are commonly up-regulated, the underlying organisms are diverse both within and across disease associated communities. Surveying DE transcripts for known ncRNAs from the Rfam database identified a large number of tRNAs and tmRNAs as well as riboswitches (FMN, glycine, lysine, and SAM) in more prevalent transcripts and the cobalamin riboswitch in both more and less prevalent transcripts. In silico discovery identified many putative ncRNAs in DE transcripts. We report 15 such putative ncRNAs having promising covariation in the predicted secondary structure and interesting genomic context. Seven of these are antisense of ribosomal proteins that are novel and may involve maintaining ribosomal protein stoichiometry during the disease associated metabolic shift. Our findings describe the role of organisms previously unaffiliated with disease and identify the commonality in progression of disease across three metatranscriptomic studies. We find that although the communities are diverse between individuals, the switch in metabolic signatures characteristic of disease is typically achieved through the contributions of several community members. Furthermore, we identify many ncRNAs (both known and putative) which may facilitate the metabolic shifts associated with periodontitis.
View details for DOI 10.3389/fmicb.2020.00482
View details for PubMedID 32328037
View details for PubMedCentralID PMC7160235
Regulatory context drives conservation of glycine riboswitch aptamers.
PLoS computational biology
2019; 15 (12): e1007564
In comparison to protein coding sequences, the impact of mutation and natural selection on the sequence and function of non-coding (ncRNA) genes is not well understood. Many ncRNA genes are narrowly distributed to only a few organisms, and appear to be rapidly evolving. Compared to protein coding sequences, there are many challenges associated with assessment of ncRNAs that are not well addressed by conventional phylogenetic approaches, including: short sequence length, lack of primary sequence conservation, and the importance of secondary structure for biological function. Riboswitches are structured ncRNAs that directly interact with small molecules to regulate gene expression in bacteria. They typically consist of a ligand-binding domain (aptamer) whose folding changes drive changes in gene expression. The glycine riboswitch is among the most well-studied due to the widespread occurrence of a tandem aptamer arrangement (tandem), wherein two homologous aptamers interact with glycine and each other to regulate gene expression. However, a significant proportion of glycine riboswitches are comprised of single aptamers (singleton). Here we use graph clustering to circumvent the limitations of traditional phylogenetic analysis when studying the relationship between the tandem and singleton glycine aptamers. Graph clustering enables a broader range of pairwise comparison measures to be used to assess aptamer similarity. Using this approach, we show that one aptamer of the tandem glycine riboswitch pair is typically much more highly conserved, and that which aptamer is conserved depends on the regulated gene. Furthermore, our analysis also reveals that singleton aptamers are more similar to either the first or second tandem aptamer, again based on the regulated gene. Taken together, our findings suggest that tandem glycine riboswitches degrade into functional singletons, with the regulated gene(s) dictating which glycine-binding aptamer is conserved.
View details for DOI 10.1371/journal.pcbi.1007564
View details for PubMedID 31860665
The Transcriptional landscape of Streptococcus pneumoniae TIGR4 reveals a complex operon architecture and abundant riboregulation critical for growth and virulence
2018; 14 (12): e1007461
Efficient and highly organized regulation of transcription is fundamental to an organism's ability to survive, proliferate, and quickly respond to its environment. Therefore, precise mapping of transcriptional units and understanding their regulation is crucial to determining how pathogenic bacteria cause disease and how they may be inhibited. In this study, we map the transcriptional landscape of the bacterial pathogen Streptococcus pneumoniae TIGR4 by applying a combination of high-throughput RNA-sequencing techniques. We successfully map 1864 high confidence transcription termination sites (TTSs), 790 high confidence transcription start sites (TSSs) (742 primary, and 48 secondary), and 1360 low confidence TSSs (74 secondary and 1286 primary) to yield a total of 2150 TSSs. Furthermore, our study reveals a complex transcriptome wherein environment-respondent alternate transcriptional units are observed within operons stemming from internal TSSs and TTSs. Additionally, we identify many putative cis-regulatory RNA elements and riboswitches within 5'-untranslated regions (5'-UTR). By integrating TSSs and TTSs with independently collected RNA-Seq datasets from a variety of conditions, we establish the response of these regulators to changes in growth conditions and validate several of them. Furthermore, to demonstrate the importance of ribo-regulation by 5'-UTR elements for in vivo virulence, we show that the pyrR regulatory element is essential for survival, successful colonization and infection in mice suggesting that such RNA elements are potential drug targets. Importantly, we show that our approach of combining high-throughput sequencing with in vivo experiments can reconstruct a global understanding of regulation, but also pave the way for discovery of compounds that target (ribo-)regulators to mitigate virulence and antibiotic resistance.
View details for DOI 10.1371/journal.ppat.1007461
View details for Web of Science ID 000454721500019
View details for PubMedID 30517198
View details for PubMedCentralID PMC6296669
Analysis of the bacteriorhodopsin-producing haloarchaea reveals a core community that is stable over time in the salt crystallizers of Eilat, Israel
2016; 20 (5): 747–57
Stability of microbial communities can impact the ability of dispersed cells to colonize a new habitat. Saturated brines and their halophile communities are presumed to be steady state systems due to limited environmental perturbations. In this study, the bacteriorhodopsin-containing fraction of the haloarchaeal community from Eilat salt crystallizer ponds was sampled five times over 3 years. Analyses revealed the existence of a constant core as several OTUs were found repeatedly over the length of the study: OTUs comprising 52 % of the total cloned and sequenced PCR amplicons were found in every sample, and OTUs comprising 89 % of the total sequences were found in more than one, and often more than two samples. LIBSHUFF and UNIFRAC analyses showed statistical similarity between samples and Spearman's coefficient denoted significant correlations between OTU pairs, indicating non-random patterns in abundance and co-occurrence of detected OTUs. Further, changes in the detected OTUs were statistically linked to deviations in salinity. We interpret these results as indicating the existence of an ever-present core bacteriorhodopsin-containing Eilat crystallizer community that fluctuates in population densities, which are controlled by salinity rather than the extinction of some OTUs and their replacement through immigration and colonization.
View details for DOI 10.1007/s00792-016-0864-4
View details for Web of Science ID 000382142400015
View details for PubMedID 27444744
Horizontal gene transfer, dispersal and haloarchaeal speciation.
Life (Basel, Switzerland)
2015; 5 (2): 1405–26
The Halobacteria are a well-studied archaeal class and numerous investigations are showing how their diversity is distributed amongst genomes and geographic locations. Evidence indicates that recombination between species continuously facilitates the arrival of new genes, and within species, it is frequent enough to spread acquired genes amongst all individuals in the population. To create permanent independent diversity and generate new species, barriers to recombination are probably required. The data support an interpretation that rates of evolution (e.g., horizontal gene transfer and mutation) are faster at creating geographically localized variation than dispersal and invasion are at homogenizing genetic differences between locations. Therefore, we suggest that recurrent episodes of dispersal followed by variable periods of endemism break the homogenizing forces of intrapopulation recombination and that this process might be the principal stimulus leading to divergence and speciation in Halobacteria.
View details for DOI 10.3390/life5021405
View details for PubMedID 25997110
View details for PubMedCentralID PMC4500145
Evidence from phylogenetic and genorne fingerprinting analyses suggests rapidly changing variation in Halorubrum and Haloarcula populations
FRONTIERS IN MICROBIOLOGY
2014; 5: 143
Halobacteria require high NaCl concentrations for growth and are the dominant inhabitants of hypersaline environments above 15% NaCl. They are well-documented to be highly recombinogenic, both in frequency and in the range of exchange partners. In this study, we examine the genetic and genomic variation of cultured, naturally co-occurring environmental populations of Halobacteria. Sequence data from multiple loci (~2500 bp) identified many closely and more distantly related strains belonging to the genera Halorubrum and Haloarcula. Genome fingerprinting using a random priming PCR amplification method to analyze these isolates revealed diverse banding patterns across each of the genera and surprisingly even for isolates that are identical at the nucleotide level for five protein coding sequenced loci. This variance in genome structure even between identical multilocus sequence analysis (MLSA) haplotypes indicates that accumulation of genomic variation is rapid: faster than the rate of third codon substitutions.
View details for DOI 10.3389/fmicb.2014.00143
View details for Web of Science ID 000334277900001
View details for PubMedID 24782838
View details for PubMedCentralID PMC3988388
Cell sorting analysis of geographically separated hypersaline environments
2013; 17 (2): 265–75
Biogeography of microbial populations remains to be poorly understood, and a novel technique of single cell sorting promises a new level of resolution for microbial diversity studies. Using single cell sorting, we compared saturated NaCl brine environments (32-35 %) of the South Bay Salt Works in Chula Vista in California (USA) and Santa Pola saltern near Alicante (Spain). Although some overlap in community composition was detected, both samples were significantly different and included previously undiscovered 16S rRNA sequences. The community from Chula Vista saltern had a large bacterial fraction, which consisted of diverse Bacteroidetes and Proteobacteria. In contrast, Archaea dominated Santa Pola's community and its bacterial fraction consisted of the previously known Salinibacter lineages. The recently reported group of halophilic Archaea, Nanohaloarchaea, was detected at both sites. We demonstrate that cell sorting is a useful technique for analysis of halophilic microbial communities, and is capable of identifying yet unknown or divergent lineages. Furthermore, we argue that observed differences in community composition reflect restricted dispersal between sites, a likely mechanism for diversification of halophilic microorganisms.
View details for DOI 10.1007/s00792-013-0514-z
View details for Web of Science ID 000315574600007
View details for PubMedID 23358730