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Knapp, B.

Publications and source records attributed to Knapp, B..

10 recordsLinked to original sources

Deletion of the gene for a cyanobacterial ribosome-associated protein affects the carbon/nitrogen metabolism

In contrast to their important structural and regulatory functions, such as in the metabolism of cyanobacteria, genes encoding small proteins are often not well characterized. Cyanobacteria use redox equivalents and energy from oxygenic photosynthesis to produce organic carbon compounds from inorganic carbon (Ci) and organic nitrogen compounds from inorganic nitrogen sources. Therefore, the assimilation and metabolism of carbon and nitrogen are coordinated at multiple levels in cyanobacteria. Here, we analyzed the Synechocystis sp. PCC 6803 gene ssr3189 encoding a 55 amino acids protein. Orthologs were detected in 665 cyanobacterial genomes defining COG5794 in the Database of Clusters of Orthologous Genes. Homologs in several eukaryotic algae suggest that Ssr3189 is an important protein that originated in cyanobacteria, was retained in algae after endosymbiosis, but was lost in plants. Polynucleotide kinase assays validated Ssr3189 as an RNA-binding protein. Deletion of ssr3189 resulted in lower pigmentation, delayed growth, and alterations in the expression of genes encoding transporters for nitrogen and Ci, and metabolic enzymes. Metabolomic analysis revealed a substantial overaccumulation of glutamine and tricarboxylic acid cycle intermediates in the deletion mutant, and further differences in the amino acid and organic acid pools compared to the wild type. Co-immunoprecipitation analysis yielded ribosomal protein S21, enolase and the Cas6-1 endoribonuclease as the most strongly co-enriched proteins, together with all other ribosomal proteins and a small set of metabolic enzymes. These findings are consistent with observations that ssr3189 encodes the ribosome-associated protein cS24 and suggest that it connects translation with metabolic control, and, potentially, RNA decay. IMPACT STATEMENTDespite considerable progress in analyzing microbial genomes, there are still substantial numbers of uncharacterized gene functions. Here, we analyzed a mutant lacking gene ssr3189 that is widely conserved, but phenotypically uncharacterized in cyanobacteria. This gene is important for growth at the optimum temperature and essential at lower temperatures. In its absence, important metabolites were overaccumulated, while genes involved in nitrogen and Ci uptake were dysregulated. The encoded protein binds RNA and interacts with proteins involved in translation and metabolism. The findings are consistent with a function as a ribosomal protein bridging protein synthesis and the regulation of metabolism.

microbiology↗

Involvement of RNase J in CRISPR RNA maturation and degradosome formation in cyanobacteria

Many bacteria and archaea use CRISPR-Cas systems, which provide RNA-based, adaptive, and inheritable immune defenses against invading viruses and other foreign genetic elements. The proper processing of CRISPR guide RNAs (crRNAs) is a crucial step in the maturation of the defense complexes and is frequently performed by specialized ribonucleases encoded by cas genes. However, some systems employ enzymes associated with degradosome or housekeeping functions, such as RNase III or the endoribonuclease RNase E. Here, the endo- and 5'-exoribonuclease RNase J was identified as an additional enzyme involved in crRNA maturation, acting jointly with RNase E in the crRNA maturation of a type III-Bv CRISPR-Cas system, and possibly together with a further RNase in the cyanobacterium Synechocystis sp. PCC 6803. Co-IP experiments revealed a small set of proteins that were co-enriched with RNase J, among them the exoribonuclease polyribonucleotide nucleotidyltransferase (PNPase). Despite a measured, strong 3 exonucleolytic activity of the recombinant enzyme, PNPase was not confirmed to contribute to crRNA maturation. However, the co-IP results indicate that PNPase in Synechocystis is an enzyme that can recruit either RNase E or RNase J, together with additional proteins.

microbiology↗

Structural basis of dual BACH1 regulation by SCFFBXO22 and SCFFBXL17

BTB and CNC homolog 1 (BACH1) is a master transcriptional regulator of the cellular oxidative stress response and pro-metastatic oncogene. Post-translational stability of BACH1 is tightly regulated by distinct F-box ubiquitin ligases, including SCFFBXO22 and SCFFBXL17. However, the molecular details have been elusive. Here, we reveal a structural switch in FBXO22 that controls the recognition of a three-dimensional degron in the BACH1 BTB domain, thus explaining its specificity for dimeric BACH1. We describe how cancer-associated mutations in FBXO22 modulate binding and ubiquitylation of BACH1. Further, we reveal that cancer-related mutations or cysteine-modifications destabilize the BTB domain and redirect BACH1 to FBXL17, where it is recognized as a monomer. This explains how complementary ligases post-translationally regulate BACH1 depending on the state of its BTB domain. Our findings provide mechanistic insights into the regulation of the oxidative stress response and may spur therapeutic strategies to targeting oxidative stress-related disorders and metastatic cancers.

biophysics↗

Metabolomic rearrangement controls the intrinsic microbial response to temperature changes

Temperature is one of the key determinants of microbial behavior and survival, whose impact is typically studied under heat- or cold-shock conditions that elicit specific regulation to combat lethal stress. At intermediate temperatures, cellular growth rate varies according to the Arrhenius law of thermodynamics without stress responses, a behavior whose origins have not yet been elucidated. Using single-cell microscopy during temperature perturbations, we show that bacteria exhibit a highly conserved, gradual response to temperature upshifts with a time scale of [~]1.5 doublings at the higher temperature, regardless of initial/final temperature or nutrient source. We find that this behavior is coupled to a temperature memory, which we rule out as being neither transcriptional, translational, nor membrane dependent. Instead, we demonstrate that an autocatalytic enzyme network incorporating temperature-sensitive Michaelis-Menten kinetics recapitulates all temperature-shift dynamics through metabolome rearrangement, which encodes a temperature memory and successfully predicts alterations in the upshift response observed under simple-sugar, low-nutrient conditions, and in fungi. This model also provides a mechanistic framework for both Arrhenius-dependent growth and the classical Monod Equation through temperature-dependent metabolite flux.

cell biology↗

Why Many Molecular Simulation Research Findings Might Be False: An Analysis of Inter-Simulations Differences Based on Simulation Time and Number of Replicas

Molecular simulations are a common technique to investigate the dynamics of proteins, DNA and RNA. A typical application is the simulation of a wild-type structure and a mutant structure where the mutant has a significantly higher (or lower) potency to trigger a signalling cascade. The study would then analyse the observed differences between the wild-type and mutant simulation and link these to their differences. However differences in the simulations cannot always be reproduced by other research groups even if the same parameters as in the original simulations are used. This is caused by the rugged energy landscape of many biological structures which means that minor differences in hardware or software can cause simulation to take different paths. This would not be a problem if the simulation time would be infinitely long but in real life the simulation time is always finite. In this study we use large scale molecular simulations of four different systems (a 10-mer peptide wild-type and mutant as well as a T-cell receptor, peptide and MHC complex as wild-type and mutant) with 100 replicas each totalling 620 000 ns to quantify the magnitude of (non-) reproducibility when comparing inter-simulation differences (e.g. wild-type vs mutant). Using a bootstrapping approach we found that simulation times of at least 2 to 3 times the experimental folding time using a minimum of 3 replicas are necessary for reproducible results. However, for most complexes of interest such long simulation times are far out of reach which means that it is only possible to sample the local phase space neighbourhood of the x-ray structure. To sample this neighbourhood reliably around 10 to 20 replicas are needed. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/504950v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@530c47org.highwire.dtl.DTLVardef@4b1aeborg.highwire.dtl.DTLVardef@d47906org.highwire.dtl.DTLVardef@155a679_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Environmental and physiological factors affecting high-throughput measurements of bacterial growth

Bacterial growth in nutrient-rich and starvation conditions is intrinsically tied to the environmental history and physiological state of the population. While high-throughput technologies have enabled rapid analyses of mutant libraries, technical and biological challenges complicate data collection and interpretation. Here, we present a framework for the execution and analysis of growth measurements with improved accuracy over standard approaches. Using this framework, we demonstrate key biological insights that emerge from consideration of culturing conditions and history. We determined that quantification of the background absorbance in each well of a multi-well plate is critical for accurate measurements of maximal growth rate. Using mathematical modeling, we demonstrated that maximal growth rate is dependent on initial cell density, which distorts comparisons across strains with variable lag properties. We established a multiple-passage protocol that alleviates the substantial effects of glycerol on growth in carbon-poor media, and we tracked growth rate-mediated fitness increases observed during a long-term evolution of Escherichia coli in low glucose concentrations. Finally, we showed that growth of Bacillus subtilis in the presence of glycerol induces a long lag in the next passage due to inhibition of a large fraction of the population. Transposon mutagenesis linked this phenotype to the incorporation of glycerol into lipoteichoic acids, revealing a new role for these envelope components in resuming growth after starvation. Together, our investigations underscore the complex physiology of bacteria during bulk passaging and the importance of robust strategies to understand and quantify growth. Abstract ImportanceHow starved bacteria adapt to and multiply in replete nutrient conditions is intimately linked to their history of previous growth, their physiological state, and the surrounding environment. While automated equipment has enabled high-throughput growth measurements, data interpretation and knowledge gaps regarding the determinants of growth kinetics complicate comparisons between strains. Here, we present a framework for growth measurements that improves accuracy and attenuates the effects of growth history. We determined that background absorbance quantification and multiple passaging cycles allows for accurate growth-rate measurements even in carbon-poor media, which we used to reveal growth-rate increases during long-term laboratory evolution of Escherichia coli. Using mathematical modeling, we showed that maximum growth rate depends on initial cell density. Finally, we demonstrated that growth of Bacillus subtilis with glycerol inhibits the future growth of most of the population, due to lipoteichoic-acid synthesis. These studies highlight the challenges of accurate quantification of bacterial growth behaviors.

microbiology↗

Towards Mycobacterium tuberculosis detection at the point-of-care: a brighter solvatochromic probe permits the detection of mycobacteria within minutes

There is an urgent need for point-of-care tuberculosis (TB) diagnostic methods that are fast, inexpensive, and operationally simple. Here, we report on a bright solvatochromic dye trehalose conjugate that specifically detects Mycobacterium tuberculosis (Mtb) in minutes. 3-hydroxychromone (3HC) dyes, known to yield high fluorescence quantum yields, exhibit shifts in fluorescence intensity in response to changes in environmental polarity. We synthesized two analogs of 3HC-trehalose conjugates (3HC-2-Tre and 3HC-3-Tre) and determined that 3HC-3-Tre has exceptionally favorable properties for Mtb detection. 3HC-3-Tre-labeled mycobacterial cells displayed a 10-fold increase in fluorescence intensity compared to our previously reports on the dye 4,4-N,N-dimethylaminonapthalimide (DMN-Tre). Excitingly, we detected fluorescent Mtb cells within 10 minutes of probe treatment. Thus, 3HC-3-Tre permits rapid visualization of mycobacteria that ultimately could empower improved Mtb detection at the point-of-care in low-resource settings.

microbiology↗

An artificial intelligence based first-line defence against COVID-19: digitally screeningcitizens for risks via a chatbot

To combat the pandemic of the coronavirus disease (COVID-19), numerous governments have established phone hotlines to prescreen potential cases. These hotlines have struggled with the volume of callers, leading to wait times of hours or, even, an inability to contact health authorities. Symptoma is a symptom-to-disease digital health assistant that can differentiate more than 20,000 diseases with an accuracy of more than 90%. We tested the accuracy of Symptoma to identify COVID-19 using a set of diverse clinical cases combined with case reports of COVID-19. We showed that Symptoma can accurately distinguish COVID-19 in 96.32% of clinical cases. When considering only COVID-19 symptoms and risk factors, Symptoma identified 100% of those infected when presented with only three signs. Lastly, we showed that Symptomas accuracy far exceeds that of simple "yes-no" questionnaires widely available online. In summary, Symptoma provides unparalleled accuracy in systematically identifying cases of COVID-19 while also considering over 20,000 other diseases. Furthermore, Symptoma allows free text input, furthered with disease-specific follow up questions, in 36 languages. Combined, these results and accessibility give Symptoma the potential to be a key tool in the global fight against COVID-19. The Symptoma predictor is freely available online at https://www.symptoma.com.

bioinformatics↗

Reassessment of the basis of cell size control based on analysis of cell-to-cell variability

Fundamental mechanisms governing cell size control and homeostasis are still poorly understood. The relationship between sizes at division and birth in single cells is used as a metric to categorize the basis of size homeostasis [1-3]. Cells dividing at a fixed size regardless of birth size (sizer) are expected to show a division-birth slope of 0, whereas cells dividing after growing for a fixed size increment (adder) have an expected slope of +1 [4]. These two theoretical values are, however, rarely experimentally observed. Here we investigate possible reasons for this discrepancy. Rod-shaped fission yeast Schizosaccharomyces pombe cells divide at a fixed surface area [5, 6], and exhibit a division-birth slope of 0.23{+/-}0.04, significantly different from the sizer value of zero. To understand whether fission yeast uses a mix of sizer and adder control, or whether size sensing is simply imprecise, we developed a mathematical model of sizer control, including the relevant sources of variation. Our results support pure sizer control and show that deviation from zero slope is exaggerated by measurement of an inappropriate geometrical quantity (e.g., length instead of area), combined with cell-to-cell radius variability. The model predicts that mutants with greater errors in size sensing or septum positioning paradoxically appear to behave as better sizers. Furthermore, accounting for cell width variability, we show that pure sizer control can in some circumstances reproduce the apparent adder behaviour observed in E. coli. These findings demonstrate that refined analysis of geometric variation can lead to new insights into cell size control.

cell biology↗

CiliaCarta: An Integrated And Validated Compendium Of Ciliary Genes

The cilium is an essential organelle at the surface of most mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We found experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins. In addition, we show that OSCP1, which has previously been implicated in two distinct non-ciliary functions, causes a cilium dysfunction phenotype when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 836 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/.

bioinformatics↗