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Zengler, K.

Publications and source records attributed to Zengler, K..

25 records · Page 2Linked to original sources

Bacterial metatranscriptomes in wastewater can differentiate virally infected human populations

Monitoring wastewater samples at building-level resolution screens large populations for SARS-CoV-2, prioritizing testing and isolation efforts. Here we perform untargeted metatranscriptomics on virally-enriched wastewater samples from 10 locations on the UC San Diego campus, demonstrating that resulting bacterial taxonomic and functional profiles discriminate SARS-CoV-2 status even without direct detection of viral transcripts. Our proof-of-principle reveals emergent threats through changes in the human microbiome, suggesting new approaches for untargeted wastewater-based epidemiology.

microbiology↗

A multiscale model predicts the sensitivity of Chlorella vulgaris to light and nitrogen levels in photobioreactors

The maximization of lipid productivity in microalgae is crucial for the biofuel industry, and it can be achieved by manipulating their metabolism. However, little efforts have been made to apply metabolic models in a dynamic framework to predict possible outcomes to scenarios observed at an industrial scale. Here, we present a dynamic framework for the simulation of large-scale photobioreactors. The framework was generated by merging the genome-scale metabolic model of Chlorella vulgaris (iCZ843) with reactor-scale parameters, thus yielding a multiscale model. This multiscale model was employed to predict the sensitivity of growth and composition variation of C. vulgaris on light and nitrogen levels. Simulations of lipid accumulation quantified the tradeoff between growth and lipid biosynthesis under nitrogen limitation. Moreover, our modeling approach quantitatively predicted the dependence of microalgal metabolism on light intensity and circadian oscillations. Finally, we use the model to design a reactor irradiance profile that maximized lipid accumulation, thus achieving a lipid productivity increase of 46% at a constant intensity of 966 E m-2 s-1. Our modeling framework elucidated how metabolism and external factors can be combined to predict optimized parameters for industrial applications.

bioengineering↗

The Prolyl-tRNA Synthetase Inhibitor Halofuginone Inhibits SARS-CoV-2 Infection

Summary ParagraphWe identify the prolyl-tRNA synthetase (PRS) inhibitor halofuginone1, a compound in clinical trials for anti-fibrotic and anti-inflammatory applications2, as a potent inhibitor of SARS-CoV-2 infection and replication. The interaction of SARS-CoV-2 spike protein with cell surface heparan sulfate (HS) promotes viral entry3. We find that halofuginone reduces HS biosynthesis, thereby reducing spike protein binding, SARS-CoV-2 pseudotyped virus, and authentic SARS-CoV-2 infection. Halofuginone also potently suppresses SARS-CoV-2 replication post-entry and is 1,000-fold more potent than Remdesivir4. Inhibition of HS biosynthesis and SARS-CoV-2 infection depends on specific inhibition of PRS, possibly due to translational suppression of proline-rich proteins. We find that pp1a and pp1ab polyproteins of SARS-CoV-2, as well as several HS proteoglycans, are proline-rich, which may make them particularly vulnerable to halofuginones translational suppression. Halofuginone is orally bioavailable, has been evaluated in a phase I clinical trial in humans and distributes to SARS-CoV-2 target organs, including the lung, making it a near-term clinical trial candidate for the treatment of COVID-19.

microbiology↗

Microbiome signatures in a fast and slow progressing gastric cancer murine model and their contribution to gastric carcinogenesis

Gastric cancer is the third most common cancer in the world and Helicobacter spp. being one of the main factors responsible for development of cancer. Alongside Helicobacter the microbiota of the stomach mucosa may also play an important role in gastric cancer progression. Previously we had established that MyD88 deficient mice rapidly progressed to neoplasia when infected with H. felis. Thus, in order to assess the role of microbiota in gastric cancer progression we measured the changes in microbial diversity of the stomach in mice with different genotypic backgrounds (Wild type (WT), MyD88 deficient (MyD88-/-), mice deficient in the Toll/IL-1R (TIR) domain-containing adaptor-inducing interferon-{beta} (TRIF, Triflps2), and MyD88 and Trif deficient (MyD88-/- and Trif-/-)double knockout (DKO) mice), both in uninfected and Helicobacter infected mice and its correlation of these changes with gastric cancer progression. We observed that there was an overall reduction in microbial diversity post infection with H. felis across all genotypes. Campylobacterales were observed in all infected mice, with marked reduction in abundance at 3 and 6 months in MyD88-/- mice. This low abundance of H. pylori could facilitate dominance of other organisms of microbiome like Lactobacilliales. A sharp increase in Lactobacilliales in infected MyD88-/- and DKO mice at 3 and 6 months was observed as compared to Trif-/- and WT mice suggesting its possible role in gastric cancer progression. This was further reinforced upon comparison of Lactobacillus ratio with histological data suggesting that Lactobacillales is closely associated with Helicobacter infection and gastric cancer progression. Thus, this study firstly suggests that difference in genotypes could define the stomach microbiome and make it more susceptible to development of gastric cancer upon Helicobacter infections. Secondly the increase in Lactobacillales could contribute to faster development of gastric cancer and serve as a probable bio marker for fast progressing form of gastric cancer.

cancer biology↗

Bacterial modification of the host glycosaminoglycan heparan sulfate modulates SARS-CoV-2 infectivity

The human microbiota has a close relationship with human disease and it remodels components of the glycocalyx including heparan sulfate (HS). Studies of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) spike protein receptor binding domain suggest that infection requires binding to HS and angiotensin converting enzyme 2 (ACE2) in a codependent manner. Here, we show that commensal host bacterial communities can modify HS and thereby modulate SARS-CoV-2 spike protein binding and that these communities change with host age and sex. Common human-associated commensal bacteria whose genomes encode HS-modifying enzymes were identified. The prevalence of these bacteria and the expression of key microbial glycosidases in bronchoalveolar lavage fluid (BALF) was lower in adult COVID-19 patients than in healthy controls. The presence of HS-modifying bacteria decreased with age in two large survey datasets, FINRISK 2002 and American Gut, revealing one possible mechanism for the observed increase in COVID-19 susceptibility with age. In vitro, bacterial glycosidases from unpurified culture media supernatants fully blocked SARS-CoV-2 spike binding to human H1299 protein lung adenocarcinoma cells. HS-modifying bacteria in human microbial communities may regulate viral adhesion, and loss of these commensals could predispose individuals to infection. Understanding the impact of shifts in microbial community composition and bacterial lyases on SARS-CoV-2 infection may lead to new therapeutics and diagnosis of susceptibility. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/238444v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@14ff1ecorg.highwire.dtl.DTLVardef@193d84corg.highwire.dtl.DTLVardef@15d6f9eorg.highwire.dtl.DTLVardef@14b16c6_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract. Diagram of hypothesis for bacterial mediation of SARS-CoV-2 infection through heparan sulfate (HS).It is well known that host microbes groom the mucosa where they reside. Recent investigations have shown that HS, a major component of mucosal layers, is necessary for SARS-CoV-2 infection. In this study we examine the impact of microbial modification of HS on viral attachment. C_FIG

microbiology↗

Nucleoid openness profiling links bacterial genome structure to phenotype

Gene expression requires specific structural alternations in the nucleoid structure to enable the access of the transcription machinery into the genomic DNA. In prokaryotes, DNA binding proteins, including nucleoid-associated proteins (NAPs) and transcription factors (TFs), drive the change in structure and gene expression. Currently, studies of global NAP and TF binding are often hindered by the lack of appropriate epigenomic tools. Here, we present POP-seq, a method that provides in vivo genome-wide openness profiles of the bacterial nucleoid. We demonstrate that POP-seq can be used to map the global in vivo protein-DNA binding events. Our results highlight a negative correlation between genome openness, compaction and transcription, suggesting that regions that are not accessible to Tn5 transposase are either too compacted or occupied by RNA polymerase. Importantly, we also show that the least open regions are enriched in housekeeping genes, while the most open regions are significantly enriched in genes important for fast adaptation to changing environment. Finally, we demonstrated that the genome openness profile is growth condition specific. Together, those results suggest a model where one can distinguish two types of epigenetic control: one stable, long-term silencing of highly compacted regions, and a second, highly responsive regulation through the dynamic competition between NAPs and RNA polymerase binding. Overall, POP-seq captures structural changes in the prokaryotic chromatin and provides condition-specific maps of global protein-DNA binding events, thus linking overall transcriptional and epigenetic regulation directly to phenotype.

microbiology↗

Deep mutational scanning by FACS-sorting of encapsulated E. coli micro-colonies

We present a method for high-throughput screening of protein variants where the signal is enhanced by micro-encapsulation of single cells into 20-30 m agarose beads. Cells inside beads are propagated using standard agitation in liquid media and grow clonally into micro-colonies harboring several hundred bacteria. We have, as a proof-of-concept, analyzed random amino acid substitutions in the five C-terminal {beta}-strands of the Green Fluorescent Protein (GFP). Starting from libraries of variants, each bead represents a clonal line of cells that can be separated by Fluorescence Activated Cell Sorting (FACS). Pools representing collections of individual variants with desired properties are subsequently analyzed by deep sequencing. Notably, the encapsulation approach described holds the potential for high-throughput analysis of systems where the fluorescence signal from a single cell is insufficient for detection. Fusion to GFP, or use of fluorogenic substrates, allows coupling protein levels or activity to sequence for a wide range of proteins. Here we analyzed more than 10,000 individual variants to gauge the effect of mutations on GFP-fluorescence. In the mutated region, we observed virtually all amino acid substitutions that are accessible by single nucleotide exchange. Lastly, we assessed the performance of biophysical protein stability predictors, FoldX and Rosetta, in predicting the outcome of the experiment. Both tools display good performance on average, suggesting that loss of thermodynamic stability is a key mechanism for the observed variation of the mutants. This, in turn, suggests that deep mutational scanning datasets may be used to more efficiently fine-tune such predictors, especially for mutations poorly covered by current biophysical data.

bioengineering↗