Insights into the regulation of malate dehydrogenase: inhibitors, activators, and allosteric modulation by small molecules.

Cellular metabolism comprises a complex network of biochemical anabolic and catabolic processes that fuel the growth and survival of living organisms. The enzyme malate dehydrogenase (MDH) is most known for its role in oxidizing malate to oxaloacetate (OAA) in the last step of the tricarboxylic acid (TCA) cycle, but it also participates in the malate-aspartate shuttle in the mitochondria as well as the glyoxylate cycle in plants. These pathways and the specific reactions within them are dynamic and must be carefully calibrated to ensure a balance between nutrient/energy supply and demand. MDH structural and functional complexity requires a variety of regulatory mechanisms, including allosteric regulation, feedback, and competitive inhibition, which are often dependent on whether the enzyme is catalyzing its forward or reverse reaction. Given the role of MDH in central metabolism and its potential as a target for therapeutics in both cancer and infectious diseases, there is a need to better understand its regulation. The involvement of MDH in multiple pathways makes it challenging to identify which effectors are critical to its activity. Many of the in vitro experiments examining MDH regulation were done decades ago, and though allosteric sites have been proposed, none to date have been specifically mapped. This review aims to provide an overview of the current knowledge surrounding MDH regulation by its substrate, products, and other intermediates of the TCA cycle while highlighting all the gaps in our understanding of its regulatory mechanisms.

External Collaboration Results in Student Learning Gains and Positive STEM Attitudes in CUREs.

The implementation of course-based undergraduate research experiences (CUREs) has made it possible to expose large undergraduate populations to research experiences. For these research experiences to be authentic, they should reflect the increasingly collaborative nature of research. While some CUREs have expanded, involving multiple schools across the nation, it is still unclear how a structured extramural collaboration between students and faculty from an outside institution affects student outcomes. In this study, we established three cohorts of students: 1) no-CURE, 2) single-institution CURE (CURE), and 3) external collaborative CURE (ec-CURE), and assessed academic and attitudinal outcomes. The ec-CURE differs from a regular CURE in that students work with faculty member from an external institution to refine their hypotheses and discuss their data. The sharing of ideas, data, and materials with an external faculty member allowed students to experience a level of collaboration not typically found in an undergraduate setting. Students in the ec-CURE had the greatest gains in experimental design; self-reported course benefits; scientific skills; and science, technology, engineering, and mathematics (STEM) importance. Importantly this study occurred in a diverse community of STEM disciplinary faculty from 2- and 4-year institutions, illustrating that exposing students to structured external collaboration is both feasible and beneficial to student learning.

Wastewater bacteria remediating the pharmaceutical metformin: Genomes, plasmids and products.

Metformin is used globally to treat type II diabetes, has demonstrated anti-ageing and COVID mitigation effects and is a major anthropogenic pollutant to be bioremediated by wastewater treatment plants (WWTPs). Metformin is not adsorbed well by activated carbon and toxic N-chloro derivatives can form in chlorinated water. Most earlier studies on metformin biodegradation have used wastewater consortia and details of the genomes, relevant genes, metabolic products, and potential for horizontal gene transfer are lacking. Here, two metformin-biodegrading bacteria from a WWTP were isolated and their biodegradation characterized. Aminobacter sp. MET metabolized metformin stoichiometrically to guanylurea, an intermediate known to accumulate in some environments including WWTPs. Pseudomonas mendocina MET completely metabolized metformin and utilized all the nitrogen atoms for growth. Pseudomonas mendocina MET also metabolized metformin breakdown products sometimes observed in WWTPs: 1-N-methylbiguanide, biguanide, guanylurea, and guanidine. The genome of each bacterium was obtained. Genes involved in the transport of guanylurea in Aminobacter sp. MET were expressed heterologously and shown to serve as an antiporter to expel the toxic guanidinium compound. A novel guanylurea hydrolase enzyme was identified in Pseudomonas mendocina MET, purified, and characterized. The Aminobacter and Pseudomonas each contained one plasmid of 160 kb and 90 kb, respectively. In total, these studies are significant for the bioremediation of a major pollutant in WWTPs today.

Development of the Organonitrogen Biodegradation Database: Teaching Bioinformatics and Collaborative Skills to Undergraduates during a Pandemic.

Physical distancing and inaccessibility to laboratory facilities created an opportunity to transition undergraduate research experiences to remote, digital platforms, adding another level of pedagogy to their training. Basic bioinformatics skills together with critical analysis of scientific literature are essential for addressing research questions in modern biology. The work presented here describes a fully online, collaborative research experience created to allow undergraduate students to learn those skills. The research experience was focused on the development and implementation of the Organonitrogen Biodegradation Database (ONDB, z.umn.edu/ondb). The ONDB was developed to catalog information about the cost, chemical properties, and biodegradation potential of commonly used organonitrogen compounds. A cross-institutional team of undergraduate researchers worked in collaboration with two faculty members and a postdoctoral fellow to develop the database. Students carried out extensive online literature searches and used a biodegradation prediction website to research and represent the microbial catabolism of different organonitrogen compounds. Participants employed computational tools such as R, Shiny, and flexdashboard to construct the database pages and interactive web interface for the ONDB. Worksheets and forms were created to encourage other students and researchers to gather information about organonitrogen compounds and expand the database. Student progress was evaluated through biweekly project meetings, presentations, and a final reflection. The ONDB undergraduate research experience provided a platform for students to learn bioinformatics skills while simultaneously developing a teaching and research tool for others.

Filling in the Gaps in Metformin Biodegradation: a New Enzyme and a Metabolic Pathway for Guanylurea.

The widely prescribed pharmaceutical metformin and its main metabolite, guanylurea, are currently two of the most common contaminants in surface and wastewater. Guanylurea often accumulates and is poorly, if at all, biodegraded in wastewater treatment plants. This study describes Pseudomonas mendocina strain GU, isolated from a municipal wastewater treatment plant, using guanylurea as its sole nitrogen source. The genome was sequenced with 36-fold coverage and mined to identify guanylurea degradation genes. The gene encoding the enzyme initiating guanylurea metabolism was expressed, and the enzyme was purified and characterized. Guanylurea hydrolase, a newly described enzyme, was shown to transform guanylurea to one equivalent (each) of ammonia and guanidine. Guanidine also supports growth as a sole nitrogen source. Cell yields from growth on limiting concentrations of guanylurea revealed that metabolism releases all four nitrogen atoms. Genes encoding complete metabolic transformation were identified bioinformatically, defining the pathway as follows: guanylurea to guanidine to carboxyguanidine to allophanate to ammonia and carbon dioxide. The first enzyme, guanylurea hydrolase, is a member of the isochorismatase-like hydrolase protein family, which includes biuret hydrolase and triuret hydrolase. Although homologs, the three enzymes show distinct substrate specificities. Pairwise sequence comparisons and the use of sequence similarity networks allowed fine structure discrimination between the three homologous enzymes and provided insights into the evolutionary origins of guanylurea hydrolase.IMPORTANCE Metformin is a pharmaceutical most prescribed for type 2 diabetes and is now being examined for potential benefits to COVID-19 patients. People taking the drug pass it largely unchanged, and it subsequently enters wastewater treatment plants. Metformin has been known to be metabolized to guanylurea. The levels of guanylurea often exceed that of metformin, leading to the former being considered a "dead-end" metabolite. Metformin and guanylurea are water pollutants of emerging concern, as they persist to reach nontarget aquatic life and humans, the latter if it remains in treated water. The present study has identified a Pseudomonas mendocina strain that completely degrades guanylurea. The genome was sequenced, and the genes involved in guanylurea metabolism were identified in three widely separated genomic regions. This knowledge advances the idea that guanylurea is not a dead-end product and will allow for bioinformatic identification of the relevant genes in wastewater treatment plant microbiomes and other environments subjected to metagenomic sequencing.

In silico Phage Hunting: Bioinformatics Exercises to Identify and Explore Bacteriophage Genomes.

Bioinformatics skills are increasingly relevant to research in most areas of the life sciences. The availability of genome sequences and large data sets provide unique opportunities to incorporate bioinformatics exercises into undergraduate microbiology courses. The goal of this project was to develop a teaching module to investigate the abundance and phylogenetic relationships amongst bacteriophages using a set of freely available bioinformatics tools. Computational identification and examination of bacteriophage genomes, followed by phylogenetic analyses, provides opportunities to incorporate core bioinformatics competencies in microbiology courses and enhance students' bioinformatics skills. The first activity consisted of using PHASTER (PHAge Search Tool Enhanced Release), a bioinformatics tool that identifies bacteriophage sequences within bacterial chromosomes. Further computational analyses were conducted to align bacteriophage proteins, genomes, and determine phylogenetic relationships amongst these viruses. This part of the project was carried out using the Clustal omega, MAFFT (Multiple Alignment using Fast Fourier Transform), and Interactive Tree of Life (iTOL) programs for sequence alignments and phylogenetic analyses. The laboratory activities were field tested in undergraduate directed research, and microbiology classes. The learning objectives were assessed by comparing the scores of pre and post-tests and grading final presentations. Post-tests were higher than pre-test scores at or below p = 0.002. The data suggest in silico phage hunting improves students' ability to search databases, interpret phylogenetic trees, and use bioinformatics tools to examine genome structure. This activity allows instructors to integrate key bioinformatic concepts in their curriculums and gives students the opportunity to participate in a research-directed learning environment in the classroom.

Complete Genome Sequence of Sinorhizobium meliloti Bacteriophage HMSP1-Susan.

Sinorhiozbium bacteriophage HMSP1-Susan has a genome of 51,963 bp in size, with a GC content of 52.5%. It contains 97 putative coding sequences; 83% of these coding sequences (CDS) encode proteins classified as hypothetical or having unknown functions. HMSP1 has limited homology to previously reported viruses and likely represents a new phage that infects this nitrogen-fixing bacterium.

Killing two birds with one stone: Model plant systems as a tool to teach the fundamental concepts of gene expression while analyzing biological data.

Plants are ideal systems to teach core biology concepts due to their unique physiological and developmental features. Advances in DNA sequencing technology and genomics have allowed scientists to generate genome sequences and transcriptomics data for numerous model plant species. This information is publicly available and presents a valuable tool to introduce undergraduate students to the fundamental concepts of gene expression in the context of modern quantitative biology and bioinformatics. Modern biology classrooms must provide authentic research experiences to allow developing core competencies such as scientific inquiry, critical interpretation of experimental results, and quantitative analyses of large dataset using computational approaches. Recent educational research has shown that undergraduate students struggle when connecting gene expression concepts to classic genetics, phenotypic analyses, and overall flow of biological information in living organisms, suggesting that novel approaches are necessary to enhance learning of gene expression and regulation. This review describes different strategies and resources available to instructors willing to incorporate authentic research experiences, genomic tools, and bioinformatics analyses when teaching transcriptional regulation and gene expression in undergraduate courses. A variety of laboratory exercises and pedagogy materials developed to teach gene expression using plants are discussed. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

An Alternative Approach to "Identification of Unknowns": Designing a Protocol to Verify the Identities of Nitrogen Fixing Bacteria.

Microbiology courses often include a laboratory activity on the identification of unknown microbes. This activity consists of providing students with microbial cultures and running biochemical assays to identify the organisms. This approach lacks molecular techniques such as sequencing of genes encoding 16S rRNA, which is currently the method of choice for identification of unknown bacteria. A laboratory activity was developed to teach students how to identify microorganisms using 16S rRNA polymerase chain reaction (PCR) and validate microbial identities using biochemical techniques. We hypothesized that designing an experimental protocol to confirm the identity of a bacterium would improve students' knowledge of microbial identification techniques and the physiological characteristics of bacterial species. Nitrogen-fixing bacteria were isolated from the root nodules of Medicago truncatula and prepared for 16S rRNA PCR analysis. Once DNA sequencing revealed the identity of the organisms, the students designed experimental protocols to verify the identity of rhizobia. An assessment was conducted by analyzing pre- and posttest scores and by grading students' verification protocols and presentations. Posttest scores were higher than pretest scores at or below p = 0.001. Normalized learning gains (G) showed an improvement of students' knowledge of microbial identification methods (LO4, G = 0.46), biochemical properties of nitrogen-fixing bacteria (LO3, G = 0.45), and the events leading to the establishment of nitrogen-fixing symbioses (LO1&2, G = 0.51, G = 0.37). An evaluation of verification protocols also showed significant improvement with a p value of less than 0.001.

Enteric pathogen-plant interactions: molecular connections leading to colonization and growth and implications for food safety.

Leafy green vegetables have been identified as a source of foodborne illnesses worldwide over the past decade. Human enteric pathogens, such as Escherichia coli O157:H7 and Salmonella, have been implicated in numerous food poisoning outbreaks associated with the consumption of fresh produce. An understanding of the mechanisms responsible for the establishment of pathogenic bacteria in or on vegetable plants is critical for understanding and ameliorating this problem as well as ensuring the safety of our food supply. While previous studies have described the growth and survival of enteric pathogens in the environment and also the risk factors associated with the contamination of vegetables, the molecular events involved in the colonization of fresh produce by enteric pathogens are just beginning to be elucidated. This review summarizes recent findings on the interactions of several bacterial pathogens with leafy green vegetables. Changes in gene expression linked to the bacterial attachment and colonization of plant structures are discussed in light of their relevance to plant-microbe interactions. We propose a mechanism for the establishment and association of enteric pathogens with plants and discuss potential strategies to address the problem of foodborne illness linked to the consumption of leafy green vegetables.

Comparative genomics of the core and accessory genomes of 48 Sinorhizobium strains comprising five genospecies.

BACKGROUND: The sinorhizobia are amongst the most well studied members of nitrogen-fixing root nodule bacteria and contribute substantial amounts of fixed nitrogen to the biosphere. While the alfalfa symbiont Sinorhizobium meliloti RM 1021 was one of the first rhizobial strains to be completely sequenced, little information is available about the genomes of this large and diverse species group. RESULTS: Here we report the draft assembly and annotation of 48 strains of Sinorhizobium comprising five genospecies. While S. meliloti and S. medicae are taxonomically related, they displayed different nodulation patterns on diverse Medicago host plants, and have differences in gene content, including those involved in conjugation and organic sulfur utilization. Genes involved in Nod factor and polysaccharide biosynthesis, denitrification and type III, IV, and VI secretion systems also vary within and between species. Symbiotic phenotyping and mutational analyses indicated that some type IV secretion genes are symbiosis-related and involved in nitrogen fixation efficiency. Moreover, there is a correlation between the presence of type IV secretion systems, heme biosynthesis and microaerobic denitrification genes, and symbiotic efficiency. CONCLUSIONS: Our results suggest that each Sinorhizobium strain uses a slightly different strategy to obtain maximum compatibility with a host plant. This large genome data set provides useful information to better understand the functional features of five Sinorhizobium species, especially compatibility in legume-Sinorhizobium interactions. The diversity of genes present in the accessory genomes of members of this genus indicates that each bacterium has adopted slightly different strategies to interact with diverse plant genera and soil environments.

Microbes in mascara: hypothesis-driven research in a nonmajor biology lab.

In this laboratory exercise, students were taught concepts of microbiology and scientific process through an everyday activity - cosmetic use. The students' goals for the lab were to develop a hypothesis regarding microbial contamination in cosmetics, learn techniques to culture and differentiate microorganisms from cosmetics, and propose best practices in cosmetics use based on their findings. Prior to the lab, students took a pretest to assess their knowledge of scientific hypotheses, microbiology, and cosmetic safety. In the first week, students were introduced to microbiological concepts and methodologies, and cosmetic terminology and safety. Students completed a hypothesis-writing exercise before formulating and testing their own hypotheses regarding cosmetic contamination. Students provided a cosmetic of their own and, in consultation with their lab group, chose one product for testing. Samples were serially diluted and plated on a variety of selective media. In the second week, students analyzed their plates to determine the presence and diversity of microbes and if their hypotheses were supported. Students completed a worksheet of their results and were given a posttest to assess their knowledge. Average test scores improved from 5.2 (pretest) to 7.8 (posttest), with p-values < 0.0001. Seventy-nine percent (79%) of students correctly identified hypotheses that were not falsifiable or lacked variables, and 89% of students improved their scores on questions concerning safe cosmetic use. Ninety-one percent (91%) of students demonstrated increased knowledge of microbial concepts and methods. Based on our results, this lab is an easy, yet effective, way to enhance knowledge of scientific concepts for nonmajors, while maintaining relevance to everyday life.

Studying gene expression: database searches and promoter fusions to investigate transcriptional regulation in bacteria.

A laboratory project was designed to illustrate how to search biological databases and utilize the information provided by these resources to investigate transcriptional regulation in Escherichia coli. The students searched several databases (NCBI Genomes, RegulonDB and EcoCyc) to learn about gene function, regulation, and the organization of transcriptional units. A fluorometer and GFP promoter fusions were used to obtain fluorescence data and measure changes in transcriptional activity. The class designed and performed experiments to investigate the regulation of genes necessary for biosynthesis of amino acids and how expression is affected by environmental signals and transcriptional regulators. Assessment data showed that this activity enhanced students' knowledge of databases, reporter genes and transcriptional regulation.

Limited functional conservation of a global regulator among related bacterial genera: Lrp in Escherichia, Proteus and Vibrio.

BACKGROUND: Bacterial genome sequences are being determined rapidly, but few species are physiologically well characterized. Predicting regulation from genome sequences usually involves extrapolation from better-studied bacteria, using the hypothesis that a conserved regulator, conserved target gene, and predicted regulator-binding site in the target promoter imply conserved regulation between the two species. However many compared organisms are ecologically and physiologically diverse, and the limits of extrapolation have not been well tested. In E. coli K-12 the leucine-responsive regulatory protein (Lrp) affects expression of approximately 400 genes. Proteus mirabilis and Vibrio cholerae have highly-conserved lrp orthologs (98% and 92% identity to E. coli lrp). The functional equivalence of Lrp from these related species was assessed. RESULTS: Heterologous Lrp regulated gltB, livK and lrp transcriptional fusions in an E. coli background in the same general way as the native Lrp, though with significant differences in extent. Microarray analysis of these strains revealed that the heterologous Lrp proteins significantly influence only about half of the genes affected by native Lrp. In P. mirabilis, heterologous Lrp restored swarming, though with some pattern differences. P. mirabilis produced substantially more Lrp than E. coli or V. cholerae under some conditions. Lrp regulation of target gene orthologs differed among the three native hosts. Strikingly, while Lrp negatively regulates its own gene in E. coli, and was shown to do so even more strongly in P. mirabilis, Lrp appears to activate its own gene in V. cholerae. CONCLUSION: The overall similarity of regulatory effects of the Lrp orthologs supports the use of extrapolation between related strains for general purposes. However this study also revealed intrinsic differences even between orthologous regulators sharing >90% overall identity, and 100% identity for the DNA-binding helix-turn-helix motif, as well as differences in the amounts of those regulators. These results suggest that predicting regulation of specific target genes based on genome sequence comparisons alone should be done on a conservative basis.

Operon information improves gene expression estimation for cDNA microarrays.

BACKGROUND: In prokaryotic genomes, genes are organized in operons, and the genes within an operon tend to have similar levels of expression. Because of co-transcription of genes within an operon, borrowing information from other genes within the same operon can improve the estimation of relative transcript levels; the estimation of relative levels of transcript abundances is one of the most challenging tasks in experimental genomics due to the high noise level in microarray data. Therefore, techniques that can improve such estimations, and moreover are based on sound biological premises, are expected to benefit the field of microarray data analysis RESULTS: In this paper, we propose a hierarchical Bayesian model, which relies on borrowing information from other genes within the same operon, to improve the estimation of gene expression levels and, hence, the detection of differentially expressed genes. The simulation studies and the analysis of experiential data demonstrated that the proposed method outperformed other techniques that are routinely used to estimate transcript levels and detect differentially expressed genes, including the sample mean and SAM t statistics. The improvement became more significant as the noise level in microarray data increases. CONCLUSION: By borrowing information about transcriptional activity of genes within classified operons, we improved the estimation of gene expression levels and the detection of differentially expressed genes.

Genome-wide localization of mobile elements: experimental, statistical and biological considerations.

BACKGROUND: The distribution and location of insertion elements in a genome is an excellent tool to track the evolution of bacterial strains and a useful molecular marker to distinguish between closely related bacterial isolates. The information about the genomic locations of IS elements is available in public sequence databases. However, the locations of mobile elements may vary from strain to strain and within the population of an individual strain. Tools that allow de novo localization of IS elements and are independent of existing sequence information are essential to map insertion elements and advance our knowledge of the role that such elements play in gene regulation and genome plasticity in bacteria. RESULTS: In this study, we present an efficient and reliable method for linear mapping of mobile elements using whole-genome DNA microarrays. In addition, we describe an algorithm for analysis of microarray data that can be applied to find DNA sequences physically juxtaposed with a target sequence of interest. This approach was used to map the locations of the IS5 elements in the genome of Escherichia coli K12. All IS5 elements present in the E. coli genome known from GenBank sequence data were identified. Furthermore, previously unknown insertion sites were predicted with high sensitivity and specificity. Two variants of E. coli K-12 MG1655 within a population of this strain were predicted by our analysis. The only significant difference between these two isolates was the presence of an IS5 element upstream of the main flagella regulator, flhDC. Additional experiments confirmed this prediction and showed that these isolates were phenotypically distinct. The effect of IS5 on the transcriptional activity of motility and chemotaxis genes in the genome of E. coli strain MG1655 was examined. Comparative analysis of expression profiles revealed that the presence of IS5 results in a mild enhancement of transcription of the flagellar genes that translates into a slight increase in motility. CONCLUSION: In summary, this work presents a case study of an experimental and analytical application of DNA microarrays to map insertion elements in bacteria and gains an insight into biological processes that might otherwise be overlooked by relying solely on the available genome sequence data.