Interaction of Acinetobacter sp. RIT 592 induces the production of broad-spectrum antibiotics in Exiguobacterium sp. RIT 594.

Antimicrobial resistance (AMR) is one of the most alarming global public health challenges of the 21st century. Over 3 million antimicrobial-resistant infections occur in the United States annually, with nearly 50,000 cases being fatal. Innovations in drug discovery methods and platforms are crucial to identify novel antibiotics to combat AMR. We present the isolation and characterization of potentially novel antibiotic lead compounds produced by the cross-feeding of two rhizosphere bacteria, Acinetobacter sp. RIT 592 and Exiguobacterium sp. RIT 594. We used solid-phase extraction (SPE) followed by liquid chromatography (LC) to enrich antibiotic extracts and subsequently mass spectrometry (MS) analysis of collected fractions for compound structure identification and characterization. The MS data were processed through the Global Natural Product Social Molecular Networking (GNPS) database. The supernatant from RIT 592 induced RIT 594 to produce a cocktail of antimicrobial compounds active against Gram-positive and negative bacteria. The GNPS analysis indicated compounds with known antimicrobial activity in the bioactive samples, including oligopeptides and their derivatives. This work emphasizes the utility of microbial community-based platforms to discover novel clinically relevant secondary metabolites. Future work includes further structural characterization and antibiotic activity evaluation of the individual compounds against pathogenic multidrug-resistant (MDR) bacteria.

Artificial intelligence tools for the identification of antibiotic resistance genes.

The fight against bacterial antibiotic resistance must be given critical attention to avert the current and emerging crisis of treating bacterial infections due to the inefficacy of clinically relevant antibiotics. Intrinsic genetic mutations and transferrable antibiotic resistance genes (ARGs) are at the core of the development of antibiotic resistance. However, traditional alignment methods for detecting ARGs have limitations. Artificial intelligence (AI) methods and approaches can potentially augment the detection of ARGs and identify antibiotic targets and antagonistic bactericidal and bacteriostatic molecules that are or can be developed as antibiotics. This review delves into the literature regarding the various AI methods and approaches for identifying and annotating ARGs, highlighting their potential and limitations. Specifically, we discuss methods for (1) direct identification and classification of ARGs from genome DNA sequences, (2) direct identification and classification from plasmid sequences, and (3) identification of putative ARGs from feature selection.

A new lysine biosynthetic enzyme from a bacterial endosymbiont shaped by genetic drift and genome reduction.

The effect of population bottlenecks and genome reduction on enzyme function is poorly understood. Candidatus Liberibacter solanacearum is a bacterium with a reduced genome that is transmitted vertically to the egg of an infected psyllid-a population bottleneck that imposes genetic drift and is predicted to affect protein structure and function. Here, we define the function of Ca. L. solanacearum dihydrodipicolinate synthase (CLsoDHDPS), which catalyzes the committed branchpoint reaction in diaminopimelate and lysine biosynthesis. We demonstrate that CLsoDHDPS is expressed in Ca. L. solanacearum and expression is increased ~2-fold in the insect host compared to in planta. CLsoDHDPS has decreased thermal stability and increased aggregation propensity, implying mutations have destabilized the enzyme but are compensated for through elevated chaperone expression and a stabilized oligomeric state. CLsoDHDPS uses a ternary-complex kinetic mechanism, which is to date unique among DHDPS enzymes, has unusually low catalytic ability, but an unusually high substrate affinity. Structural studies demonstrate that the active site is more open, and the structure of CLsoDHDPS with both pyruvate and the substrate analogue succinic-semialdehyde reveals that the product is both structurally and energetically different and therefore evolution has in this case fashioned a new enzyme. Our study suggests the effects of genome reduction and genetic drift on the function of essential enzymes and provides insights on bacteria-host co-evolutionary associations. We propose that bacteria with endosymbiotic lifestyles present a rich vein of interesting enzymes useful for understanding enzyme function and/or informing protein engineering efforts.

Whole-genome sequencing of four culturable endophytic bacteria from German hardneck garlic cloves (Allium sativum L.).

We present the whole-genome sequence of four bacterial endophytes associated with German hardneck garlic cloves (Allium sativum L.). Among them, Agrobacterium fabrum and Pantoea agglomerans are associated with plant protection, while Rahnella perminowiae and Stenotrophomonas lactitubi are pathogens. These data will facilitate the identification of genes to improve garlic.

Enzyme Kinetics Analysis: An online tool for analyzing enzyme initial rate data and teaching enzyme kinetics.

Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and cellular biology to pharmacology. However, because enzyme kinetics involves concepts rarely employed in other areas of biology, it can be challenging for students and researchers. Traditional graphical analysis was replaced by computational analysis, requiring another skill not core to many life sciences curricula. Computational analysis can be time-consuming and difficult in free software (e.g., R) or require costly software (e.g., GraphPad Prism). We present Enzyme Kinetics Analysis (EKA), a web-tool to augment teaching and learning and streamline EKA. EKA is an interactive and free tool for analyzing enzyme kinetic data and improving student learning through simulation, built using R and RStudio's ShinyApps. EKA provides kinetic models (Michaelis-Menten, Hill, simple reversible inhibition models, ternary-complex, and ping-pong) for users to fit experimental data, providing graphical results and statistics. Additionally, EKA enables users to input parameters and create data and graphs, to visualize changes to parameters (e.g., K M or number of measurements). This function is designed for students learning kinetics but also for researchers to design experiments. EKA (enzyme-kinetics.shinyapps.io/enzkinet_webpage/) provides a simple, interactive interface for teachers, students, and researchers to explore enzyme kinetics. It gives researchers the ability to design experiments and analyze data without specific software requirements.

Isolation, whole-genome sequencing, and annotation of two antibiotic-producing and antibiotic-resistant bacteria, Pantoea rodasii RIT 836 and Pseudomonas endophytica RIT 838, collected from the environment.

Antimicrobial resistance (AMR) is a global threat to human health since infections caused by antimicrobial-resistant bacteria are life-threatening conditions with minimal treatment options. Bacteria become resistant when they develop the ability to overcome the compounds that are meant to kill them, i.e., antibiotics. The increasing number of resistant pathogens worldwide is contrasted by the slow progress in the discovery and production of new antibiotics. About 700,000 global deaths per year are estimated as a result of drug-resistant infections, which could escalate to nearly 10 million by 2050 if we fail to address the AMR challenge. In this study, we collected and isolated bacteria from the environment to screen for antibiotic resistance. We identified several bacteria that showed resistance to multiple clinically relevant antibiotics when tested in antibiotic susceptibility disk assays. We also found that two strains, identified as Pantoea rodasii RIT 836 and Pseudomonas endophytica RIT 838 via whole genome sequencing and annotation, produce bactericidal compounds against both Gram-positive and Gram-negative bacteria in disc-diffusion inhibitory assays. We mined the two strains' whole-genome sequences to gain more information and insights into the antibiotic resistance and production by these bacteria. Subsequently, we aim to isolate, identify, and further characterize the novel antibiotic compounds detected in our assays and bioinformatics analysis.

Endophytic bacteria associated with wild-type banana seed (Musa balbisiana): whole genome sequencing.

We present the whole-genome sequences of five endophytic bacteria isolated from Musa balbisiana seeds. These strains represent five different genera: Bacillus, Brachybacterium, Enterobacter, Enterococcus, and Pantoea. Among these, three genera (Bacillus, Pantoea, and Enterobacter) were previously recognized for their antagonistic effects against Fusarium wilt, a highly destructive disease that affects banana plants.

Chromatographic isolation of potentially novel antibiotic compounds produced by Yimella sp. RIT 621.

OBJECTIVE: Antibiotic resistant infections have become a global health crisis causing 1.2 million deaths worldwide in 2019 [1]. In a previous study, we identified a bacterium from a rare genus, Yimella, and found in an initial antibiotic screening that they produce broad-spectrum bactericidal compounds [2]. Herein, we focus on the characterization of these potential novel antimicrobial compounds produced by Yimella sp. RIT 621. RESULTS: We used solid-phase extraction and C18 reverse-phase chromatography to isolate the antibiotic-active compounds found in organic extracts from liquid cultures of Yimella sp. RIT 621. We tracked the antimicrobial activity by testing the extracts in disc diffusion inhibitory assays and observed its increase after each purification stage.

Whole-Genome Sequence of Endophytic Bacteria Associated with Poison Ivy Vine (Toxicodendron radicans).

Here, we report the genome assemblies of 11 endophytic bacteria, isolated from poison ivy vine (Toxicodendron radicans). Five species belonging to the genus Pseudomonas, two species of Curtobacterium, one strain of Pantoea agglomerans, and one species from the Bacillus, Cellulomonas, and Enterobacter genera were isolated from the interior tissue of poison ivy.

Whole-Genome Sequence, Assembly and Annotation of an Invasive Plant, Lonicera maackii (Amur Honeysuckle).

The invasive species Lonicera maackii (Amur Honeysuckle) is an increasing problem sweeping from the eastern United States toward the west, impacting normal forest development and animal survival across multiple taxa. Little is known about the genomics of this species, although a related invasive, Lonicera japonica, has been sequenced. Understanding the genomic foundation of the Lonicera maackii species could help us understand the biochemistry and life history that are the underpinnings of invasive success, as well as potential vulnerabilities and strengths which could guide research and development to control its spread. Here we present a draft, but high-quality, short-read whole-genome sequence, assembly, and annotation of Lonicera maackii, demonstrating that inexpensive and rapid short-read technologies can be successfully used in invasive species research. Despite being a short-read assembly, the genome length (7.93 × 108) and completeness (estimated as 90.2-92.1% by BUSCO and Merqury) are close to the previously published chromosome-level sequencing of L. japonica. No bias, by means of a Gene Ontology analysis, was identified among missing BUSCOs. A duplication of the 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase gene in both Lonicera species is identified, and the potential impact on controlling these invasive species is discussed. Future prospects for a diversity analysis of invasive species is also discussed.

Draft Genome Sequences of Three Antibiotic-Producing Soil Bacteria, Staphylococcus pasteuri WAM01, Peribacillus butanolivorans WAM04, and Micrococcus yunnanensis WAM06, with Growth-Inhibiting Effects against Commensal Neisseria Strains.

We report the isolation, identification, and assemblies of three antibiotic-producing soil bacteria (Staphylococcus pasteuri, Peribacillus butanolivorans, and Micrococcus yunnanensis) that inhibit the growth of Neisseria commensals in coculture. With pathogenic Neisseria strains becoming increasingly resistant to antibiotics, bioprospecting for novel antimicrobials using commensal relatives may facilitate discovery of clinically useful drugs.

Isolation, Whole-Genome Sequencing, and Annotation of Two Antibiotic-Producing and -Resistant Bacteria, Enterobacter roggenkampii RIT 834 and Acinetobacter pittii RIT 835, from Disposable Masks Collected from the Environment.

We report the whole-genome sequence and annotation of two antibiotic-resistant bacteria, Enterobacter roggenkampii RIT 834 and Acinetobacter pittii RIT 835, isolated from disposed masks. We found that these strains are resistant to five of seven commonly used antibiotics and that they produce bactericidal compounds against Escherichia coli.

Polystyrene Degradation by Exiguobacterium sp. RIT 594: Preliminary Evidence for a Pathway Containing an Atypical Oxygenase.

The widespread use of plastics has led to their increasing presence in the environment and subsequent pollution. Some microorganisms degrade plastics in natural ecosystems and the associated metabolic pathways can be studied to understand the degradation mechanisms. Polystyrene (PS) is one of the more recalcitrant plastic polymers that is degraded by only a few bacteria. Exiguobacterium is a genus of Gram-positive poly-extremophilic bacteria known to degrade PS, thus being of biotechnological interest, but its biochemical mechanisms of degradation have not yet been elucidated. Based solely on genome annotation, we initially proposed PS degradation by Exiguobacterium sp. RIT 594 via depolymerization and epoxidation catalyzed by a ring epoxidase. However, Fourier transform infrared (FTIR) spectroscopy analysis revealed an increase of carboxyl and hydroxyl groups with biodegradation, as well as of unconjugated C-C double bonds, both consistent with dearomatization of the styrene ring. This excludes any aerobic pathways involving side chain epoxidation and/or hydroxylation. Subsequent experiments confirmed that molecular oxygen is critical to PS degradation by RIT 594 because degradation ceased under oxygen-deprived conditions. Our studies suggest that styrene breakdown by this bacterium occurs via the sequential action of two enzymes encoded in the genome: an orphan aromatic ring-cleaving dioxygenase and a hydrolase.

Evolutionary paths to macrolide resistance in a Neisseria commensal converge on ribosomal genes through short sequence duplications.

Neisseria commensals are an indisputable source of resistance for their pathogenic relatives. However, the evolutionary paths commensal species take to reduced susceptibility in this genus have been relatively underexplored. Here, we leverage in vitro selection as a powerful screen to identify the genetic adaptations that produce azithromycin resistance (≥ 2 µg/mL) in the Neisseria commensal, N. elongata. Across multiple lineages (n = 7/16), we find mutations that reduce susceptibility to azithromycin converge on the locus encoding the 50S ribosomal L34 protein (rpmH) and the intergenic region proximal to the 30S ribosomal S3 protein (rpsC) through short tandem duplication events. Interestingly, one of the laboratory evolved mutations in rpmH is identical (7LKRTYQ12), and two nearly identical, to those recently reported to contribute to high-level azithromycin resistance in N. gonorrhoeae. Transformations into the ancestral N. elongata lineage confirmed the causality of both rpmH and rpsC mutations. Though most lineages inheriting duplications suffered in vitro fitness costs, one variant showed no growth defect, suggesting the possibility that it may be sustained in natural populations. Ultimately, studies like this will be critical for predicting commensal alleles that could rapidly disseminate into pathogen populations via allelic exchange across recombinogenic microbial genera.

Function and evolution of B-Raf loop dynamics relevant to cancer recurrence under drug inhibition.

Oncogenic mutations in the kinase domain of the B-Raf protein have long been associated with cancers involving the MAPK pathway. One constitutive MAPK activating mutation in B-Raf, the V600E (valine to glutamate) replacement occurring adjacent to a site of threonine phosphorylation (T599) occurs in many types of cancer, and in a large percentage of certain cancers, such as melanoma. Because ATP binding activity and the V600E mutation are both known to alter the physical behavior of the activation loop in the B-Raf ATP binding domain, this system is especially amenable to comparative analyses of molecular dynamics simulations modeling various genetic and drug class variants. Here, we employ machine learning enabled identification of functionally conserved protein dynamics to compare how the binding interactions of four B-Raf inhibitors impact the functional loop dynamics controlling ATP activation. We demonstrate that drug development targeting B-Raf has progressively moved towards ATP competitive inhibitors that demonstrate less tendency to mimic the functionally conserved dynamic changes associated with ATP activation and leading to the side effect of hyperactivation (i.e. inducing MAPK activation in non-tumorous cells in the absence of secondary mutation). We compare the functional dynamic impacts of V600E and other sensitizing and drug resistance causing mutations in the regulatory loops of B-Raf, confirming sites of low mutational tolerance in these regions. Lastly, we investigate V600E sensitivity of B-Raf loop dynamics in an evolutionary context, demonstrating that while sensitivity has an ancient origin with primitive eukaryotes, it was also secondarily increased during early jawed vertebrate evolution.Communicated by Ramaswamy H. Sarma.

Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent Betacoronavirus strains.

Comparative functional analysis of the dynamic interactions between various Betacoronavirus mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. A multi-agent classifier successfully identified functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Conserved dynamics regions of ACE2 involve both the N-terminal helices, as well as a region of more transient dynamics encompassing residues K353, Q325 and a novel motif AAQPFLL 386-92 that appears to coordinate their dynamic interactions with the viral RBD at N501. We also demonstrate that the functional evolution of Betacoronavirus zoonotic spillovers involving ACE2 interaction dynamics are likely pre-adapted from two precise and stable binding sites involving the viral bat progenitor strain's interaction with CD26 at SAMLI 291-5 and SS 333-334. Our analyses further indicate that the human endemic strains hCoV-HKU1 and hCoV-OC43 have evolved more stable N-terminal helix interactions through enhancement of an interfacing loop region on the viral RBD, whereas the highly transmissible SARS-CoV-2 variants (B.1.1.7, B.1.351 and P.1) have evolved more stable viral binding via more focused interactions between the viral N501 and ACE2 K353 alone.Communicated by Ramaswamy H. Sarma.

Isolation, Whole-Genome Sequencing, and Annotation of Three Unclassified Antibiotic-Producing Bacteria, Enterobacter sp. Strain RIT 637, Pseudomonas sp. Strain RIT 778, and Deinococcus sp. Strain RIT 780.

We report the isolation, whole-genome sequencing, and annotation of Enterobacter sp. strain RIT 637, Pseudomonas sp. strain RIT 778, and Deinococcus sp. strain RIT 780. Disk diffusion assays using spent medium demonstrated that all bacteria produced bactericidal compounds against Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, and Staphylococcus aureus ATCC 25923.

Exiguobacterium sp. is endowed with antibiotic properties against Gram positive and negative bacteria.

OBJECTIVE: In order to isolate and identify bacteria that produce potentially novel bactericidal/bacteriostatic compounds, two ponds on the campus of the Rochester Institute of Technology (RIT) were targeted as part of a bioprospecting effort. RESULTS: One of the unique isolates, RIT 452 was identified as Exiguobacterium sp. and subjected to whole-genome sequencing. The genome was assembled and in silico analysis was performed to predict the secondary metabolite gene clusters, which suggested the potential of Exiguobacterium RIT452 for producing antibiotic compounds. Extracts of spent growth media of RIT452 were active in disc diffusion assays performed against four reference strains, two Gram-negative (E. coli ATCC 25922 and P. aeruginosa ATCC 27853) and two Gram-positive (B. subtilis BGSC 168 and S. aureus ATCC 25923). Differential extraction and liquid chromatography was used to fractionate the extracts. Efforts to identify and elucidate the structure of the active compound(s) are still ongoing.

Genomic characterization of bacteria from the ultra-oligotrophic Madison aquifer: insight into the archetypical LuxI/LuxR and identification of novel LuxR solos.

OBJECTIVES: To characterize the bacterial community of Wind Cave's Madison aquifer through whole-genome sequencing, and to better understand the bacterial ecology by identifying genes involved in acyl-homoserine lactone (AHL) based quorum-sensing (QS) systems. RESULTS: Genome-based taxonomic classification revealed the microbial richness present in the pristine Madison aquifer. The strains were found to span eleven genera and fourteen species, of which eight had uncertain taxonomic classifications. The genomes of strains SD129 and SD340 were found to contain the archetypical AHL QS system composed of two genes, luxI and luxR. Surprisingly, the genomes of strains SD115, SD129, SD274 and SD316 were found to contain one to three luxR orphans (solos). Strain SD129, besides possessing an archetypical AHL QS luxI-luxR pair, also contained two luxR solos, while strain SD316 contained three LuxR solos and no luxI-luxR pairs. The ligand-binding domain of two LuxR solos, one each from strains SD129 and SD316, were found to contain novel substitutions not previously reported, thus may represent two LuxR orphans that detection and response to unknown self-produced signal(s), or to signal(s) produced by other organisms.

Whole-Genome Sequencing and Annotation of 10 Endophytic and Epiphytic Bacteria Isolated from Lolium arundinaceum.

We report the whole-genome sequence and annotation of 10 endophytic and epiphytic bacteria isolated from the grass Lolium arundinaceum as part of a laboratory exercise in a Fundamentals of Plant Biochemistry and Pathology undergraduate course (BIOL403) at the Rochester Institute of Technology in Rochester, New York.