Biology subjects

Molenaar, D.

Publications and source records attributed to Molenaar, D..

8 recordsLinked to original sources

bioRxiv2022

Genetic elements orchestrating Lactobacillus crispatus glycogen metabolism in the vagina

Glycogen in the female lower reproductive tract is a major carbon source for vaginal colonization and acidification by common vaginal Lactobacillus species, such as Lactobacillus crispatus. Previously we identified the pullulanase gene pulA in Lactobacillus crispatus, correlating with its ability to autonomously utilize glycogen for growth. Here we further characterize genetic variation and differential regulation of pulA affecting the presence of its gene product on the outer surface layer. We show that alpha-glucan degrading activity dissipates when Lactobacilllus crispatus is grown on glucose, maltose and maltotriose, in agreement with carbon catabolite repression elements flanking the pulA gene. Proteome analysis of the S-layer confirmed that the pullulanase protein is highly abundant in an S-layer enriched fraction, but not in a strain with a defective pullulanase variant or in a pullulanase-sufficient strain grown on glucose. In addition, we provide evidence that Lactobacillus crispatus pulA mutants are relevant in vivo, as they are commonly observed in metagenome datasets of human vaginal microbial communities. Analysis of the largest publicly available human vaginal metagenome dataset indicates that 15 out of 272 samples, containing a Lactobacillus crispatus pulA gene, contain a defective variant of this gene. Another 23 out of 272 samples show large deletions or transposon insertions. Taken together, these results demonstrate that both environmental as well as genetic factors explain variation of Lactobacillus crispatus alpha-glucosidases in the vaginal environment.

microbiology↗

bioRxiv2021

A simple coloring method to distinguish colonies of the yeasts Lachancea thermotolerans and Saccharomyces cerevisiae on agar media

The yeast Lachancea thermotolerans converts consumed sugar partly to lactic acid instead of ethanol and is therefore used together with Saccharomyces cerevisiae to produce wines with a lower alcohol content. Being able to distinguish these yeasts is important for quality control and quantitative assessment of the contributions of both yeasts to wine fermentations. Commonly used methods to routinely distinguish these organisms are indirect or rely on commercial products of undisclosed composition. Here we describe that adding bromocresol purple to agar media induces Lachancea colonies to develop a brown color, whereas Saccharomyces colonies remain white.

microbiology↗

bioRxiv2020

Proteome constraints reveal targets for improving microbial fitness in nutrient-rich environments

Cells adapt to different conditions via gene expression that tunes metabolism and stress resistance for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs1; Resource allocation under proteome constraints has emerged as a powerful paradigm to explain regulatory strategies in bacteria2. It is unclear, however, to what extent these constraints can predict evolutionary changes, especially for microorganisms that evolved under nutrient-rich conditions, i.e., multiple available nitrogen sources, such as the lactic acid bacterium Lactococcus lactis. Here we present an approach to identify preferred nutrients from integration of experimental data with a proteome-constrained genome-scale metabolic model of L. lactis (pcLactis), which explicitly accounts for gene expression processes and associated constraints. Using glucose-limited chemostat data3, we identified the uptake of glucose and arginine as dominant constraints, whose pathway proteins were indeed upregulated in evolved mutants. However, above a growth rate of 0.5 h-1, pcLactis suggests that available enzymes function at their maximum capacity, which allows an increase in growth rate only by altering gene expression to change metabolic fluxes, as was mainly observed for arginine metabolism. Thus, our integrative analysis of flux and proteomics data with a proteome-constrained model is able to identify and explain the constraints that form targets of regulation and fitness improvement in nutrient-rich growth environments.

systems biology↗

bioRxiv2020

Biodiversity and niche partitioning in an anaerobic benzene degrading culture

A key question in microbial ecology is what the driving forces behind the persistence of large biodiversity in natural environments are. We studied a microbial community with more than 100 different types of species which evolved in a 15-years old bioreactor with benzene as the main carbon and free energy source and nitrate as the electron acceptor. We demonstrate that only a few community members are able to degrade benzene, and that most of the others feed on the metabolic left-overs or on the contents of dead cells making up a food web with different trophic levels. As a result of niche partitioning, a high species richness is maintained and the complexity of a natural community is stabilized in a relatively simple environment. This view highlights the importance of species interactions and interdependencies, which drive microbial community structure and function. These mechanisms may well be conserved across ecosystems.

ecology↗

bioRxiv2019

A Systematic Assessment Of Current Genome-Scale Metabolic Reconstruction Tools

Several genome-scale metabolic reconstruction software platforms have been developed and are being continuously updated. These tools have been widely applied to reconstruct metabolic models for hundreds of microorganisms ranging from important human pathogens to species of industrial relevance. However, these platforms, as yet, have not been systematically evaluated with respect to software quality, best potential uses and intrinsic capacity to generate high-quality, genome-scale metabolic models. It is therefore unclear for potential users which tool best fits the purpose of their research. In this work, we performed a systematic assessment of the current genome-scale reconstruction software platforms. To meet our goal, we first defined a list of features for assessing software quality related to genome-scale reconstruction, which we expect to be useful for the potential users of these tools. Subsequently, we used the feature list to evaluate the performance of each tool. In order to assess the similarity of the draft reconstructions to high-quality models, we compared each tools output networks with that of the high-quality, manually curated, models of Lactobacillus plantarum and Bordetella pertussis, representatives of gram-positive and gram-negative bacteria, respectively. We showed that none of the tools outperforms the others in all the defined features and that model builders should carefully choose a tool (or combinations of tools) depending on the intended use of the metabolic model. Author SummaryMetabolic networks that comprise biochemical reactions at genome-scale have become very useful to study and predict the phenotype of important microorganisms. Several software platforms exist to build these metabolic networks. Based on different approaches and utilizing a variety of databases it is, unfortunately, unclear what are the best scenarios to use each of these tools. Hence, to understand the potential uses of these tools, we created a list of relevant features for metabolic reconstruction and we evaluated the tools in all these categories. Here, we show that none of the tools is better than the other in all the evaluated categories; instead, each tool is more suitable for particular purposes. Therefore, users should carefully select the tool(s) that best fit the purpose of their research. This is the first time these tools are systematically evaluated and this overview can be used as a guide for selecting the correct tool(s) for each case.

systems biology↗

bioRxiv2018

Integrated Stress Response Deregulation underlies Vanishing White Matter and is a target for therapy

Vanishing white matter (VWM) is a fatal, stress-sensitive leukodystrophy that mainly affects children and is currently without treatment. VWM is caused by recessive mutations in eukaryotic initiation factor 2B (eIF2B) that is crucial for initiation of mRNA translation and its regulation under stress conditions. Mice with bi-allelic missense mutations in eIF2B recapitulate human VWM. VWM pathomechanisms are unclear. Using polysomal profiling to screen for mRNAs with altered translation we observed most prominent changes in expression of integrated stress response (ISR) mRNAs in brains of mutant compared to wild-type mice; expression levels correlated with disease severity. We substantiated these findings in VWM patients brains. ISRIB, an ISR inhibitor, normalized expression of mRNA markers, ameliorated white matter pathology and improved motor skills in VWM mice, thus showing that the ISR is central in VWM pathomechanisms and a viable target for therapy.\n\nOne Sentence SummaryISRIB ameliorates ISR deregulation and clinical signs in VWM mice

neuroscience↗

bioRxiv2018

Comparative genomics of human Lactobacillus crispatus isolates reveals genes for glycosylation and glycogen degradation: Implications for in vivo dominance of the vaginal microbiota

BackgroundA vaginal microbiota dominated by lactobacilli (particularly Lactobacillus crispatus) is associated with vaginal health, whereas a vaginal microbiota not dominated by lactobacilli is considered dysbiotic. Here we investigated whether L. crispatus strains isolated from the vaginal tract of women with Lactobacillus-dominated vaginal microbiota (LVM) are pheno- or genotypically distinct from L. crispatus strains isolated from vaginal samples with dysbiotic vaginal microbiota (DVM).\n\nResultsWe studied 33 L. crispatus strains (n=16 from LVM; n=17 from DVM). Comparison of these two groups of strains showed that, although strain differences existed, both groups were heterofermentative, produced similar amounts of organic acids, inhibited Neisseria gonorrhoeae growth and did not produce biofilms. Comparative genomics analyses of 28 strains (n=12 LVM; n=16 DVM) revealed a novel, 3-fragmented glycosyltransferase gene that was more prevalent among strains isolated from DVM. Most L. crispatus strains showed growth on glycogen-supplemented growth media. Strains that showed less efficient (n=6) or no (n=1) growth on glycogen all carried N-terminal deletions (respectively, 29 and 37 amino acid-deletions) in a putative pullulanase type I gene.\n\nDiscussionL. crispatus strains isolated from LVM were not phenotypically distinct from L. crispatus strains isolated from DVM, however, the finding that the latter were more likely to carry a 3-fragmented glycosyltransferase gene may indicate a role for cell surface glycoconjugates, which may shape vaginal microbiota-host interactions. Furthermore, the observation that variation in the pullulanase type I gene associated with growth on glycogen discourages previous claims that L. crispatus cannot directly utilize glycogen.

microbiology↗

bioRxiv2017

Glucose limitation in Lactococcus shapes a single-peaked fitness landscape exposing membrane occupancy as a constraint

A central theme in biology is to understand the molecular basis of fitness: which strategies succeed under which conditions; how are they mechanistically implemented; and which constraints shape trade-offs between alternative strategies. We approached these questions with parallel bacterial evolution experiments in chemostats. Chemostats provide a constant environment with a defined resource limitation (glucose), in which the growth rate can be controlled. Using Lactococcus lactis, we found a single mutation in a global regulator of carbon metabolism, CcpA, to confer predictable fitness improvements across multiple growth rates. In silico protein structural analysis complemented with biochemical and phenotypic assays, show that the mutation reprograms the CcpA regulon, specifically targeting transporters. This supports that membrane occupancy, rather than biosynthetic capacity, is the dominant constraint for the observed fitness enhancement. It also demonstrates that cells can modulate a pleiotropic regulator to work around limiting constraints.

genomics↗