Search NASA⌕ Search

SEARCH · Search NASA

Results for “disease severity analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Sequence Analysis of 20,453 Severe Acute Respiratory Syndrome Coronavirus 2 Genomes from the Houston Metropolitan Area Identifies the Emergence and Widespread Distribution of Multiple Isolates of All Major Variants of Concern

Since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, there has been international concern about the emergence of virus variants with mutations that increase transmissibility, enhance escape from the human immune response, or otherwise alter biologically important phenotypes. In late 2020, several variants of concern emerged globally, including the UK variant (B.1.1.7), the South Africa variant (B.1.351), Brazil variants (P.1 and P.2), and two related California variants of interest (B.1.429 and B.1.427). These variants are believed to have enhanced transmissibility. For the South Africa and Brazil variants, there is evidence that mutations in spike protein permit it to escape from some vaccines and therapeutic monoclonal antibodies. On the basis of our extensive genome sequencing program involving 20,453 coronavirus disease 2019 patient samples collected from March 2020 to February 2021, we report identification of all six of these SARS-CoV-2 variants among Houston Methodist Hospital (Houston, TX) patients residing in the greater metropolitan area. Although these variants are currently at relatively low frequency (aggregate of 1.1%) in the population, they are geographically widespread. Houston is the first city in the United States in which active circulation of all six current variants of concern has been documented by genome sequencing. Finally, as vaccine deployment accelerates, increased genomic surveillance of SARS-CoV-2 is essential to understanding the presence, frequency, and medical impact of consequential variants and their patterns and trajectory of dissemination.

60 APPLIED LIFE SCIENCES↗

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗

Silencing Folylpolyglutamate Synthetase1 (FPGS1) in Switchgrass (Panicum virgatum L.) Improves Lignocellulosic Biofuel Production

Switchgrass (Panicum virgatum L.) is a lignocellulosic perennial grass with great potential in bioenergy field. Lignocellulosic bioenergy crops are mostly resistant to cell wall deconstruction, and therefore yield suboptimal levels of biofuel. The one-carbon pathway (also known as C1 metabolism) is critical for polymer methylation, including that of lignin and hemicelluloses in cell walls. Folylpolyglutamate synthetase (FPGS) catalyzes a biochemical reaction that leads to the formation of folylpolyglutamate, an important cofactor for many enzymes in the C1 pathway. In this study, the putatively novel switchgrass PvFPGS1 gene was identified and its functional role in cell wall composition and biofuel production was examined by RNAi knockdown analysis. The PvFPGS1-downregulated plants were analyzed in the field over three growing seasons. Transgenic plants with the highest reduction in PvFPGS1 expression grew slower and produced lower end-of-season biomass. Transgenic plants with low-to-moderate reduction in PvFPGS1 transcript levels produced equivalent biomass as controls. There were no significant differences observed for lignin content and syringyl/guaiacyl lignin monomer ratio in the low-to-moderately reduced PvFPGS1 transgenic lines compared with the controls. Similarly, sugar release efficiency was also not significantly different in these transgenic lines compared with the control lines. However, transgenic plants produced up to 18% more ethanol while maintaining congruent growth and biomass as non-transgenic controls. Severity of rust disease among transgenic and control lines were not different during the time course of the field experiments. Altogether, the unchanged lignin content and composition in the low-to-moderate PvFPGS1-downregulated lines may suggest that partial downregulation of PvFPGS1 expression did not impact lignin biosynthesis in switchgrass. In conclusion, the manipulation of PvFPGS1 expression in bioenergy crops may be useful to increase biofuel potential with no growth penalty or increased susceptibility to rust in feedstock.

59 BASIC BIOLOGICAL SCIENCES↗

Role of Tensile Stress in DNA Nanoresonators for Epigenetic Studies

The evaluation of epigenetic features such as DNA methylation is becoming increasingly important in many biochemical processes like gene expression and transcription as well as in several diseases like schizophrenia or diabetes. Here, in this work, we report that self-assembled nanomechanical resonators entirely composed of DNA molecules can be used to explore gross changes in DNA methylation levels (0–25–50%), while careful control of tensile stress is needed to reduce the variability of resonance frequency for rigorous quantification. The effect of the tensile stress retained by the suspended DNA nanoresonators on the application of the technique is extensively explored using a combination of laser Doppler vibrometry and atomic force spectroscopy. DNA nanoresonators are real-time, label-free sensors and could avoid chemical functionalization and sample amplification. Therefore, they may represent in the future a key complementary routine tool for global DNA methylation analysis needed to evaluate the consequences of environmental stresses on the human genome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flaxseed oil ameliorates aging in d ‐galactose induced rats via altering gut microbiota and mitigating oxidative damage

Abstract BACKGROUND Aging causes decreased antioxidant capacity and chronic inflammation and may even elevate cancer risks. Previous studies reported that flaxseed oil (FO) can alleviate age‐related diseases, including improving alcoholic liver disease, atherosclerosis and diabetes. However, whether the intestinal microbiota accountable for this alleviation is still unknown. This study aims to study the antioxidant effects of FO in an aging rat model and the underlying mechanism between the intestinal microbiota and aging. RESULTS Our results presented that serum and liver antioxidant capacities in FO group were up‐regulated, and liver inflammation in FO group was reduced. The 16S rDNA sequencing showed that FO regulated the microbial community, including up‐regulation of four families of Lactobacillus and six families of Clostridium. In addition, FO had also adjusted the relative abundance of several genera such as Ruminococcaceae_UCG‐005 and Prevotella_9 , which may be the key bacteria associated with the aging process. Colonic transcriptome analysis showed that there were 1679 differentially expressed genes (DEGs) in the Model group and the FO group (134 up‐regulated and 1545 down‐regulated). Gene set enrichment analysis (GSEA) revealed FO down‐regulates the expression of the upstream genes Ptprc , Lck , Zap70 , Lat and Lcp2 in the T cell receptor signaling pathway. CONCLUSION In conclusion, FO improved antioxidant capacity and reduced intestinal microbial disturbances caused by aging damage, indicating that dietary FO has the potential to fight aging damage. This study provides a more comprehensive view of dietary intervention to improve aging. © 2022 Society of Chemical Industry.

Sun, Xiaoyan↗

Differential Regulation of Maize and Sorghum Orthologs in Response to the Fungal Pathogen Exserohilum turcicum

Pathogens that infect more than one host offer an opportunity to study how resistance mechanisms have evolved across different species. Exserohilum turcicum infects both maize and sorghum and the isolates are host-specific, offering a unique system to examine both compatible and incompatible interactions. We conducted transcriptional analysis of maize and sorghum in response to maize-specific and sorghum-specific E. turcicum isolates and identified functionally related co-expressed modules. Maize had a more robust transcriptional response than sorghum. E. turcicum responsive genes were enriched in core orthologs in both crops, but only up to 16% of core orthologs showed conserved expression patterns. Most changes in gene expression for the core orthologs, including hub genes, were lineage specific, suggesting a role for regulatory divergent evolution. We identified several defense-related shared differentially expressed (DE) orthologs with conserved expression patterns between the two crops, suggesting a role for parallel evolution of those genes in both crops. Many of the differentially expressed genes (DEGs) during the incompatible interaction were related to quantitative disease resistance (QDR). This work offers insights into how different hosts with relatively recent divergence interact with a common pathogen. Our results are important for developing resistance to this critical pathogen and understanding the evolution of host-pathogen interactions.

54 ENVIRONMENTAL SCIENCES↗

Use of virus‐induced gene silencing to characterize genes involved in modulating hypersensitive cell death in maize

Abstract Plant disease resistance proteins (R‐proteins) detect specific pathogen‐derived molecules, triggering a defence response often including a rapid localized cell death at the point of pathogen penetration called the hypersensitive response (HR). The maize Rp1‐D21 gene encodes a protein that triggers a spontaneous HR causing spots on leaves in the absence of any pathogen. Previously, we used fine mapping and functional analysis in a Nicotiana benthamiana transient expression system to identify and characterize a number of genes associated with variation in Rp1‐D21 ‐induced HR. Here we describe a system for characterizing genes mediating HR, using virus‐induced gene silencing (VIGS) in a maize line carrying Rp1‐D21 . We assess the roles of 12 candidate genes. Three of these genes, SGT1 , RAR1 , and HSP90 , are required for HR induced by a number of R‐proteins across several plant–pathogen systems. We confirmed that maize HSP90 was required for full Rp1‐D21 ‐induced HR. However, suppression of SGT1 expression unexpectedly increased the severity of Rp1‐D21 ‐induced HR while suppression of RAR1 expression had no measurable effect. We confirmed the effects on HR of two genes we had previously validated in the N. benthamiana system, hydroxycinnamoyltransferase and caffeoyl CoA O‐methyltransferase . We further showed the suppression the expression of two previously uncharacterized, candidate genes, IQ calmodulin binding protein ( IQM3 ) and vacuolar protein sorting protein 37 , suppressed Rp1‐D21 ‐induced HR. This approach is an efficient way to characterize the roles of genes modulating the hypersensitive defence response and other dominant lesion phenotypes in maize.

59 BASIC BIOLOGICAL SCIENCES↗

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3 , the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC ) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1 . Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

59 BASIC BIOLOGICAL SCIENCES↗

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

59 BASIC BIOLOGICAL SCIENCES↗

Epidemiological surveillance of common respiratory viruses in patients with suspected COVID-19 in Southwest China

Abstract Background The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the peak season of common respiratory viral infections. However, the clinical symptoms of most SARS-CoV-2 infected patients are not significantly different from those of common respiratory viral infections. Therefore, knowing the epidemiological patterns of common respiratory viruses may be valuable to improve the diagnostic and therapeutic efficacy of patients with suspected COVID-19, especially in Southwest China (a mild epidemic area). Methods A total of 2188 patients with clinically suspected of COVID-19 in Southwest China were recruited from January 21 to February 29, 2020. Nasopharyngeal swabs, throat swabs and sputum specimens were collected to detect SARS-CoV-2 by using real-time reverse transcription-polymerase chain reaction (RT-PCR) and other 12 viruses via PCR fragment analysis combined with capillary electrophoresis. Clinical characteristics and laboratory test findings were acquired from electronic medical records. All data were analyzed to unravel the epidemiological patterns. Results Only 1.1% (24/2188) patients with suspected COVID-19 were eventually confirmed to have SARS-CoV-2 infection, and the most frequently observed symptoms were fever (75.0%, 18/24) and cough (20.8%, 5/24). The overall detection rate of other respiratory pathogens was 10.3% (226/2188). Among them, human rhinovirus (3.2%, 71/2188), human parainfluenza viruses (1.6%, 35/2188), influenza B virus (1.2%, 26/2188) and mycoplasma pneumonia (1.2%, 26/2188) were the predominantly detected pathogens in this study. Moreover, the co-infection was observed in 22 specimens. Notably, one COVID-19 case had a coexisting infection with human parainfluenza virus (4.2%, 1/24) and bocavirus was the most common virus tending to occur in co-infection with other respiratory pathogens. Conclusions This study reveals the epidemiological features of common respiratory viruses and their clinical impact during the ongoing outbreak of COVID-19 in a mild epidemic area. The findings highlight the importance of understanding the transmission patterns of the common respiratory virus in COVID-19 regions, which can provide information support for the development of appropriate treatment plans and health policies, while eliminating unnecessary fear and tension.

Si, Yanjun↗

The development and use of decision support framework for informing selection of select agent toxins with modelling studies to inform permissible toxin amounts

Many countries have worked diligently to establish and implement policies and processes to regulate high consequence pathogens and toxins that could have a significant public health impact if misused. In the United States, the Antiterrorism and Effective Death Penalty Act of 1996 (Public Law 104-132, 1996), as amended by the Bioterrorism Preparedness and Response Act of 2002 (Public Law 107-188, 2002) requires that the Department of Health and Human Services (HHS) [through the Centers for Disease Control and Prevention (CDC)] establish a list of bacteria, viruses, and toxins that have the potential to pose a severe threat to public health and safety. Currently, this list is reviewed and updated on a biennial basis using input from subject matter experts (SMEs). We have developed decision support framework (DSF) approaches to facilitate selection of select toxins and, where toxicity data are known, conducted modelling studies to inform selection of toxin amounts that should be excluded from select agent regulations. Exclusion limits allow laboratories to possess toxins under an established limit to support their research or teaching activities without the requirement to register with the Federal Select Agent Program. Fact sheets capturing data from a previously vetted SME workshop convened by CDC, literature review and SME input were developed to assist in evaluating toxins using the DSF approach. The output of the DSF analysis agrees with the current select toxin designations, and no other toxins evaluated in this study were recommended for inclusion on the select agent and toxin list. To inform the selection of exclusion limits, attack scenarios were developed to estimate the amount of toxin needed to impact public health. Scenarios consisted of simulated aerosol releases of a toxin in high-population-density public facilities and the introduction of a toxin into a daily consumable product supply chain. Using published inhalation and ingestion median toxic dose (TD 50 ) and median lethal dose (LD 50 ) values, where available, a range of toxin amounts was examined to estimate the number of people exposed to these amounts in these scenarios. Based on data generated by these models, we proposed toxin exclusion values corresponding to levels below those that would trigger a significant public health response (i.e., amounts estimated to expose up to ten people by inhalation or one hundred people by ingestion to LD 50 or TD 50 levels of toxin in the modeled scenarios).

60 APPLIED LIFE SCIENCES↗

Tunable White Light for Elders (TWLITE): A Protocol Demonstrating Feasibility and Acceptability for Deployment, Remote Data Collection, and Analysis of a Home-Based Lighting Intervention in Older Adults

Sleep disturbances are common in older adults and may contribute to disease progression in certain populations (e.g., Alzheimer’s disease). Light therapy is a simple and cost-effective intervention to improve sleep. Primary barriers to light therapy are: (1) poor acceptability of the use of devices, and (2) inflexibility of current devices to deliver beyond a fixed light spectrum and throughout the entirety of the day. However, dynamic, tunable lighting integrated into the native home lighting system can potentially overcome these limitations. Herein, we describe our protocol to implement a whole-home tunable lighting system installed throughout the homes of healthy older adults already enrolled in an existing study with embedded home assessment platforms (Oregon Center for Aging & Technology—ORCATECH). Within ORCATECH, continuous data on room location, activity, sleep, and general health parameters are collected at a minute-to-minute resolution over years of participation. This single-arm longitudinal protocol collected participants’ light usage in addition to ORCATECH outcome measures over a several month period before and after light installation. The protocol was implemented with four subjects living in three ORCATECH homes. Technical/usability challenges and feasibility/acceptability outcomes were explored. The successful implementation of our protocol supports the feasibility of implementing and integrating tunable whole-home lighting systems into an automated home-based assessment platform for continuous data collection of outcome variables, including long-term sleep measures. Challenges and iterative approaches are discussed. This protocol will inform the implementation of future clinical intervention trials using light therapy in patients at risk for developing Alzheimer’s disease and related conditions.

60 APPLIED LIFE SCIENCES↗

Six Machine-Learning Methods for Predicting Hospital-Stay Duration for Patients with Sepsis: A Comparative Study

Sepsis is a life-threatening medical condition that, if not treated promptly, can result in tissue damage, organ failure, and death. According to the Centers for Disease Control, about 270,000 individuals die of sepsis in the US each year. Further, sepsis expenditures accounted for 13% of total US hospital costs in 2013, totaling more than $24 billion. Our project objectives were to determine if Machine Learning algorithms could reliably predict hospital stay duration for patients with sepsis. The data set we used has been de-identified and is freely available through the BupaR package. The data includes 1050 cases, 15214 events, and 16 types of actions related to sepsis patient care. First, we used process mining to determine how long each patient was in the hospital. Using BupaR’s functions, we created several process model graphs. These process models depict the movement of patients at a hospital and provide duration data for each patent case. Second, we identified outlier data and created two dataset versions: one with and one without outliers. We then applied the following analysis methods: Linear Regression, Random Forest, K-Nearest Neighbors, Neural Networks, XGBoost, and lightGBM. We compared the model validations for the six machine learning models using the same data-splitting method. We found that the XGBoost model had the best prediction accuracy of 73.9 percent for cases with outliers, and 79 percent for cases without outliers. We also found that the lightGBM model had the lowest mean absolute error between prediction and actual duration in days with 3.66 days for the case with outliers, and 2.4 days for the case without outliers. These two models outperformed the other four models. This work will be enhanced in the future by exploring new prediction algorithms and comparing them with the results of this study.

Chen, Lingtao↗

Staged progression epidemic models for the transmission of invasive nontyphoidal Salmonella (iNTS) with treatment

We develop and analyze a stage-progression compartmental model to study the emerging invasive nontyphoidal Salmonella (iNTS) epidemic in sub-Saharan Africa. iNTS bloodstream infections are often fatal, and the diverse and non-specific clinical features of iNTS make it difficult to diagnose. We focus our study on identifying approaches that can reduce the incidence of new infections. In sub-Saharan Africa, transmission and mortality are correlated with the ongoing HIV epidemic and severe malnutrition. We use our model to quantify the impact that increasing antiretroviral therapy (ART) for HIV infected adults and reducing malnutrition in children would have on mortality from iNTS in the population. We consider immunocompromised subpopulations in the region with major risk factors for mortality, such as malaria and malnutrition among children and HIV infection and ART coverage in both children and adults. We parameterize the progression rates between infection stages using the branching probabilities and estimated time spent at each stage. We interpret the basic reproduction number R 0 as the total contribution from an infinite infection loop produced by the asymptomatic carriers in the infection chain. The results indicate that the asymptomatic HIV+ adults without ART serve as the driving force of infection for the iNTS epidemic. We conclude that the worst disease outcome is among the pediatric population, which has the highest infection rates and death counts. Our sensitivity analysis indicates that the most effective strategies to reduce iNTS mortality in the studied population are to improve the ART coverage among high-risk HIV+ adults and reduce malnutrition among children.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring inflammation‐related protein expression and its relationship with TSPO PET in Alzheimer's disease

Abstract INTRODUCTION To understand the role of neuroinflammation in Alzheimer's disease (AD), we characterized immune‐related proteins in central and peripheral biofluids. METHODS Selection of participants from the Translational Biomarker of Aging and Dementia (TRIAD) cohort with available translocator protein (TSPO) positron emission tomography (PET), cerebrospinal fluid (CSF) (n = 97), and plasma (n = 165). Biofluid samples analyzed with Olink technology (368 inflammation proteins). RESULTS Elevated proteins levels in CSF of TSPO‐positive individuals were identified. Functional enrichment analysis of CSF proteins revealed processes implicated in AD (MAPK, ERK cascades, cytokine, and leukocyte signaling). Selected candidates (CXCL1 and TNFRSF11B) showed high correlation with each other in CSF and with TSPO PET signal, but weaker associations with amyloid and tau PET. No significantly changed proteins in plasma between TSPO groups were found. DISCUSSION This explorative study identified two potential targets in CSF showing correlations with TSPO, amyloid and tau PET, suggesting a direct link between neuroinflammation, expression of these proteins and their potential implication in AD. Highlights Several proteins are elevated in CSF of TSPO PET‐positive individuals, linking them to neuroinflammation. Elevated CSF proteins were enriched in pathways such as MAPK, ERK, and cytokine signaling, linking them to the AD pathophysiology. Candidate proteins (CXCL1 and TNFRSF11B) correlated strongly with TSPO PET, particularly in brain regions known to be affected in AD. Although none of the plasma proteins remained significant after multiple comparisons correction when comparing their expression between TSPO groups, as done for CSF, candidate CSF proteins were found to correlate with plasmatic proteins, highlighting the complexity of the immune system.

Neurosciences & Neurology↗

Antimicrobial resistance and genomic characterization of Salmonella Dublin isolates in cattle from the United States

Salmonella enterica subspecies enterica serotype Dublin is a host-adapted serotype in cattle, associated with enteritis and systemic disease. The primary clinical manifestation of Salmonella Dublin infection in cattle, especially calves, is respiratory disease. While rare in humans, it can cause severe illness, including bacteremia, with hospitalization and death. In the United States, S . Dublin has become one of the most multidrug-resistant serotypes. The objective of this study was to characterize S . Dublin isolates from sick cattle by analyzing phenotypic and genotypic antimicrobial resistance (AMR) profiles, the presence of plasmids, and phylogenetic relationships. S . Dublin isolates (n = 140) were selected from submissions to the NVSL for Salmonella serotyping (2014–2017) from 21 states. Isolates were tested for susceptibility against 14 class-representative antimicrobial drugs. Resistance profiles were determined using the ABRicate with Resfinder and NCBI databases, AMRFinder and PointFinder. Plasmids were detected using ABRicate with PlasmidFinder. Phylogeny was determined using vSNP. We found 98% of the isolates were resistant to more than 4 antimicrobials. Only 1 isolate was pan-susceptible and had no predicted AMR genes. All S . Dublin isolates were susceptible to azithromycin and meropenem. They showed 96% resistance to sulfonamides, 97% to tetracyclines, 95% to aminoglycosides and 85% to beta-lactams. The most common AMR genes were: sulf2 and tetA (98.6%), aph(6)-Id (97.9%), aph(3’’)-Ib, (97.1%), floR (94.3%), and blaCMY-2 (85.7%). All quinolone resistant isolates presented mutations in gyr A. Ten plasmid types were identified among all isolates with IncA/C2, IncX1, and IncFII(S) being the most frequent. The S . Dublin isolates show low genomic genetic diversity. This study provided antimicrobial susceptibility and genomic insight into S . Dublin clinical isolates from cattle in the U.S. Further sequence analysis integrating food and human origin S . Dublin isolates may provide valuable insight on increased virulence observed in humans.

60 APPLIED LIFE SCIENCES↗

Different chemical scaffolds bind to L-phe site in Mycobacterium tuberculosis Phe-tRNA synthetase

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mt), is one of the deadliest infectious diseases. The rise of multidrug-resistant strains represents a major public health threat, requiring new therapeutic options. Bacterial aminoacyl-tRNA synthetases (aaRS) have been shown to be highly promising drug targets, including for TB treatment. These enzymes play an essential role in translating the DNA gene code into protein sequence by attaching specific amino acid to their cognate tRNAs. They have multiple binding sites that can be targeted for inhibitor discovery: amino acid binding pocket, ATP binding pocket, tRNA binding site and an editing domain. Recently we reported several high-resolution structures of M. tuberculosis phenylalanyl-tRNA synthetase (MtPheRS) complexed with tRNA Phe and either L-Phe or a nonhydrolyzable phenylalanine adenylate analog. Here, in this study, using Nucleic Magnetic Resonance (NMR) and Surface Plasmon Resonance (SPR) we identified fragments that bind to MtPheRS and we determined crystal structures of their complexes with MtPheRS/tRNA Phe . All the binders interact with the L-Phe amino acid binding site. The analysis of interactions of the new compounds combined with adenylate analog structure provides insights for the rational design of antituberculosis drugs. The 3 ' arm of the tRNA Phe in all the structures was disordered with exception of one complex with D-735 compound. In this structure the 3' CCA end of the acceptor stem is observed in the editing domain of MtPheRS providing insights regarding the post-transfer editing activity of class II aaRS.

Gade, Priyanka [Univ. of Chicago, IL (United State↗