Biology subjects

Katz, S.

Publications and source records attributed to Katz, S..

7 recordsLinked to original sources

bioRxiv2021

Selective whole genome amplification as a tool to enrich specimens with low Treponema pallidum genomic DNA copies for whole genome sequencing

Downstream next generation sequencing (NGS) of the syphilis spirochete Treponema pallidum subspecies pallidum (T. pallidum) is hindered by low bacterial loads and the overwhelming presence of background metagenomic DNA in clinical specimens. In this study, we investigated selective whole genome amplification (SWGA) utilizing multiple displacement amplification (MDA) in conjunction with custom oligonucleotides with an increased specificity for the T. pallidum genome, and the capture and removal of CpG-methylated host DNA using the NEBNext(R) Microbiome DNA Enrichment Kit followed by MDA with the REPLI-g Single Cell Kit as enrichment methods to improve the yields of T. pallidum DNA in isolates and lesion specimens from syphilis patients. Sequencing was performed using the Illumina MiSeq v2 500 cycle or NovaSeq 6000 SP platform. These two enrichment methods led to 93-98% genome coverage at 5 reads/site in 5 clinical specimens from the United States and rabbit propagated isolates, containing >14 T. pallidum genomic copies/l of sample for SWGA and >129 genomic copies/l for CpG methylation capture with MDA. Variant analysis using sequencing data derived from SWGA-enriched specimens, showed that all 5 clinical strains had the A2058G mutation associated with azithromycin resistance. SWGA is a robust method that allows direct whole genome sequencing (WGS) of specimens containing very low numbers of T. pallidum, which have been challenging until now. ImportanceSyphilis is a sexually transmitted, disseminated acute and chronic infection caused by the bacterial pathogen Treponema pallidum subspecies pallidum. Primary syphilis typically presents as single or multiple mucocutaneous lesions, and if left untreated, can progress through multiple stages with varied clinical manifestations. Molecular studies often rely on direct amplification of DNA sequences from clinical specimens; however, this can be impacted by inadequate samples due to disease progression or timing of patients seeking clinical care. While genotyping has provided important data on circulating strains over the past two decades, WGS data is needed to better understand strain diversity, perform evolutionary tracing, and monitor antimicrobial resistance markers. The significance of our research is the development of a SWGA DNA enrichment method that expands the range of clinical specimens that can be directly sequenced to include samples with low numbers of T. pallidum.

genomics↗

bioRxiv2021

Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains

Although closely related genetically, bacterial strains belonging to the same species show significant variability in their growth and death dynamics. However, our understanding of the underlying processes that lead to this variability is still lacking. Here, we measured the growth and death dynamics of 11 strains of E. coli originating from different hosts and developed a mathematical model that captures their growth and death dynamics. Our model considers two environmental factors that determine growth dynamics: resource utilization efficiency and density-dependent growth inhibition. Here we show that both factors are required to capture the measured dynamics. Interestingly, our model results indicate that the main process that determines the major differences between the strains is the critical density at which they slow down their growth, rather than maximal growth rate or death rate. Finally, we found that bacterial growth and death dynamics can be reduced to only two dimensions and described by death rates and density-dependent growth inhibition alone. ImportanceUnderstanding the dynamics of bacterial growth has been an area of intense study. However, these dynamics have often been characterized through the narrow prism of describing growth rates, without considering parameters that may modulate these rates. Here, we generate a model that describes bacterial growth and death dynamics, incorporating two essential, growth-modulating factors: density-dependent reductions in growth rates and resource utilization efficiency. This model allows us to demonstrate that variation in the growth curves of closely related bacterial strains can be reduced to two dimensions and explained almost entirely by variation in the cellular density at which bacteria slow down their growth, combined with their death rates.

microbiology↗

bioRxiv2020

Culture volume influences the dynamics of adaptation under long-term stationary phase

Escherichia coli and many other bacterial species, which are incapable of sporulation, can nevertheless survive within resource exhausted media by entering a state termed long-term stationary phase (LTSP). We have previously shown that E. coli populations adapt genetically under LTSP in an extremely convergent manner. Here we examine how the dynamics of LTSP genetic adaptation are influenced by varying a single parameter of the experiment - culture volume. We find that culture volume affects survival under LTSP, with viable counts decreasing as volumes increase. Across all volumes, mutations accumulate with time, and the majority of mutations accumulated demonstrate signals of being adaptive. However, positive selection appears to affect mutation accumulation more strongly at higher, compared to lower volumes. Finally, we find that several similar genes are likely involved in adaptation across volumes. However, the specific mutations within these genes that contribute to adaptation can vary in a consistent manner. Combined, our results demonstrate how varying a single parameter of an evolutionary experiment can substantially influence the dynamics of observed adaptation.

evolutionary biology↗

bioRxiv2020

Dynamics of mutation accumulation and adaptation during three years of evolution under long-term stationary phase

Many bacterial species that cannot sporulate, such as the model bacterium Escherichia coli, can nevertheless survive for years under resource exhaustion, in a state termed long-term stationary phase (LTSP). Here we describe the dynamics of E. coli adaptation during the first three years spent under LTSP. We show that during this time E. coli continuously adapts genetically, through the accumulation of mutations. For non-mutator clones, the majority of mutations accumulated appear to be adaptive under LTSP, reflected in an extremely convergent pattern of mutation accumulation. Despite the rapid and convergent manner in which populations adapt under LTSP, they continue to harbor extensive genetic variation. The dynamics of evolution of mutation rates under LTSP are particularly interesting. The emergence of mutators, affects overall mutation accumulation rates as well as the mutational spectra and the ultimate spectrum of adaptive alleles acquired under LTSP. With time, mutators can evolve even higher mutation rates, through the acquisition of additional mutation-rate enhancing mutations. Different mutator and non-mutator clones within a single population and time point can display extreme variation in their mutation rates, resulting in differences in both the dynamics of adaptation and their associated deleterious burdens. Despite these differences, clones that vary greatly in their mutation rates tend to co-exist within their populations for many years, under LTSP.

evolutionary biology↗

bioRxiv2020

TRIAGE: A web-based iterative analysis platform integrating pathway and network databases optimizes hit selection from high- throughput assays.

Comprehensive and efficient gene hit selection from high throughput assays remains a critical bottleneck in realizing the potential of genome-scale studies in biology. Widely used methods such as setting of cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions offer divergent solutions yet are associated with critical analytical trade-offs, and are often combined in an ad hoc manner. The specific limitations of these individual approaches, the lack of a systematic way by which to integrate their rankings, and the inaccessibility of complex computational approaches to many researchers, has contributed to unexpected variability and limited overlap in the reported results from comparable genome-wide studies. Using a set of three highly studied genome-wide datasets for HIV host factors that have been broadly cited for their limited number of shared candidates, we characterize the specific complementary contributions of commonly used analysis approaches and find an optimal framework by which to integrate these methods. We describe Throughput Ranking by Iterative Analysis of Genomic Enrichment (TRIAGE), an integrated, iterative approach which uses pathway and network statistical methods and publicly available databases to optimize gene prioritization. TRIAGE is accessible as a secure, rapid, user-friendly web-based application (https://triage.niaid.nih.gov). O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/204917v2_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@7150f8org.highwire.dtl.DTLVardef@17af411org.highwire.dtl.DTLVardef@12d8f01org.highwire.dtl.DTLVardef@78c48_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

bioinformatics↗

bioRxiv2020

Adaptations accumulated under prolonged resource exhaustion are highly transient

Many non-sproulating bacterial species can survive for years within exhausted growth media in a state termed long-term stationary phase (LTSP). We have been carrying out evolutionary experiments aimed at elucidating the dynamics of genetic adaptation under LTSP. We showed that Escherichia coli adapts to prolonged resource exhaustion through the highly convergent acquisition of mutations. In the most striking example of such convergent adaptation, we observed that across all independently evolving LTSP populations, over 90% of E. coli cells carry mutations to one of three specific sites of the RNA polymerase core enzyme (RNAPC). These LTSP adaptations reduce the ability of the cells carrying them to grow once fresh resources are again provided. Here, we examine how LTSP populations recover from costs associated with their adaptation, once resources are again provided to them. We demonstrate that due to the ability of LTSP populations to maintain high levels of standing genetic variation during adaptation, costly adaptations are very rapidly purged from the population once they are provided with fresh resources. We further demonstrate that recovery from costs acquired during adaptation under LTSP occurs much more rapidly than would be possible if LTSP adaptations had fixed during the time populations spent under resource exhaustion. Finally, we previously reported that under LTSP, some clones develop a mutator phenotype, greatly increasing their mutation accumulation rates. Here, we show that the mechanisms, by which populations recover from costs associated with fixed adaptations, may depend on mutator status.

evolutionary biology↗

bioRxiv2020

Phosphorylation of Threonine 107 by Calcium/Calmodulin dependent Kinase II δ Regulates the Detoxification Efficiency and Proteomic Integrity of Glyoxalase 1

The glyoxalase system is a ubiquitously expressed enzyme system with narrow substrate specificity and is responsible for the detoxification of harmful methylglyoxal (MG), a spontaneous by-product of energy metabolism. Glyoxalase 1 (Glo1) is the first and therefore rate limiting enzyme of this protective system. In this study we were able to show that a phosphorylation of threonine-107 in the Glo1 protein, mediated by Ca2+/Calmodulin-dependent Kinase II delta (CamKII{delta}), is associated with elevated catalytic efficiency of Glo1. In fact, Michaelis-Menten kinetics of Glo1 mutants revealed that a permanent phosphorylation of Glo1 was associated with increased Vmax (1.23 {micro}mol/min/mg) and decreased Km (0.19 mM HTA), whereas the non-phosphorylatable Glo1 showed significantly lower Vmax (0.66 {micro}mol/min/mg) and increased Km (0.31 mM HTA). This was also confirmed with human recombinant Glo1 (Vmax (Glo1phos) = 999 {micro}mol/min/mg; Km (Glo1phos) = 0.09 mM HTA vs. Vmax (Glo1red) = 497 {micro}mol/min/mg; Km (Glo1red) = 0.12 mM HTA). Additionally, proteasomal degradation of non-phosphorylated Glo1 via ubiquitination occurred more rapidly as compared to native Glo1. The absence of the responsible kinase CamKII{delta} was associated with poor MG detoxification capacity and decreased protein content of Glo1 in a murine CamKII{delta} knock-out model. Furthermore, this regulatory mechanism is also related to an altered Glo1 status in cancer, diabetes and during aging. In summary, phosphorylation of threonine-107 in the Glo1 protein by CamKII{delta} is a quick and precise mechanism regulating Glo1 activity.

molecular biology↗