Biology subjects

Zimmermann, M.

Publications and source records attributed to Zimmermann, M..

54 records · Page 3Linked to original sources

bioRxiv2023

Emergence of community behaviors in the gut microbiota upon drug treatment

Pharmaceuticals can directly inhibit the growth of gut bacteria, but the degree such interactions manifest in complex community settings is an open question. Here we compared the effects of 30 drugs on a 32-species synthetic community with their effects on each community member in isolation. While most individual drug-species interactions remained the same in the community context, communal behaviors emerged in 26% of all tested cases. Cross-protection, during which drug-sensitive species became protected in community, was 6-times more frequent than cross-sensitization, the converse phenomenon. Cross-protection decreased and cross-sensitization increased at higher drug concentrations, suggesting that the resilience of microbial communities can collapse when perturbations get stronger. By metabolically profiling drug-treated communities, we showed that both drug biotransformation and bioaccumulation contribute mechanistically to communal protection. As a proof-of-principle, we molecularly dissected a prominent case: species expressing specific nitroreductases degraded niclosamide, thereby protecting both themselves and sensitive community members.

microbiology↗

bioRxiv2023

Contribution of cortical layers to human dynamic functional connectivity

Transitory states of the brain, sometimes linked to particular mental disorders, can be identified by conducting a dynamic analysis of connectivity in functional magnetic resonance imaging (fMRI) data. Here, we investigated whether the connectivity between cortical laminae (in contrast to between cortical areas), can vary during the course of a resting-state scan and whether this could impact the identification of brain states in the healthy brain. We performed a sliding-window connectivity analysis of high-resolution fMRI data and found that the differential participation of the cortical layers in the overall cortical connectivity constitutes a more dynamic feature of the brain compared to region-to-region connectivity, with two main states (superficial vs. deep-laminae connectivity) fluctuating over time. Laminar connectivity restricted to the default mode network appeared relatively stable (superficial connectivity preferred), while the central executive and salience networks showed a fluctuating laminar preference. We anticipate that the dynamic analysis of connectivity focused on the different depths of the cerebral cortex could play an important role in characterizing healthy brain states as well as in identifying novel targets of psychiatric diseases.

neuroscience↗

bioRxiv2022

Multiomics and quantitative modelling disentangle diet, host, and microbiota contributions to the host metabolome

Dietary nutrients, host metabolism, and gut microbiota activity each influence the hosts metabolic phenotype; however, the interplay between these factors remains poorly understood. We employed tissue-resolved metabolomics in gnotobiotic mice carrying a synthetic human gut microbiota and germfree mice in two dietary conditions to develop an intestinal flux model that quantifies diet, host, and bacterial contributions to the levels of 2,700 intestinal metabolites. While diet was the main factor affecting metabolite profiles, we identified 1,117 potential microbial substrates and products in the gut. By integrating metagenomics and metatranscriptomics data into genome-scale enzymatic networks, we linked 202 potential substrate-product pairs by a single enzymatic reaction. We further identified bacterial species and enzymes that can explain the differential abundance of 13% of the identified microbial products between the mouse groups. This quantitative modelling approach paves the way for controlling an individuals metabolic phenotype by modulating their gut microbiome composition and diet.

systems biology↗

bioRxiv2021

Guiding ATR and PARP inhibitor combinations with chemogenomic screens

Combinations of inhibitors of Ataxia Telangiectasia- and Rad3-related kinase (ATRi) and poly(ADP-ribose) polymerases (PARPi) synergistically kill tumor cells through modulation of complementary DNA repair pathways, but their tolerability is limited by hematological toxicities. To address this we performed a genome-wide CRISPR/Cas9 screen to identify genetic alterations that hypersensitize cells to a combination of the ATRi RP-3500 with PARPi, including deficiency in RNase H2, RAD51 paralog mutations or the Alternative Lengthening of Telomeres telomere maintenance mechanism. We show that RP-3500 and PARPi combinations kill cells carrying these genetic alterations at doses sub-therapeutic as single agents. We also demonstrate the mechanism of combination hypersensitivity in RNase H2-deficient cells, where we observe an irreversible replication catastrophe, allowing us to design a highly efficacious and tolerable in vivo dosing schedule. Altogether, we present a comprehensive dataset to inform development of ATRi and PARPi combinations and an experimental framework applicable to other drug combination strategies.

cancer biology↗

bioRxiv2021

Entrectinib - a SARS-CoV-2 inhibitor in Human Lung Tissue (HLT) cells

Since the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify potential drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a promising antiviral drug. We found that part of the antiviral action of entrectinib is mediated by a non-specific mechanism, likely occurring at the viral membrane level. Such a profile could provide entrectinib with protection against the development of drug resistance by emerging SARS-CoV-2 variants.

cell biology↗

bioRxiv2020

MetaGraph: Indexing and Analysing Nucleotide Archives at Petabase-scale

The amount of biological sequencing data available in public repositories is growing exponentially, forming an invaluable biomedical research resource. Yet, making it full-text searchable and easily accessible to researchers in life and data science is an unsolved problem. In this work, we take advantage of recently developed, very efficient data structures and algorithms for representing sequence sets. We make Petabases of DNA sequences across all clades of life, including viruses, bacteria, fungi, plants, animals, and humans, fully searchable. Our indexes are freely available to the research community. This highly compressed representation of the input sequences (up to 5800x) fits on a single consumer hard drive ({approx}100 USD), making this valuable resource cost-effective to use and easily transportable. We present the underlying methodological framework, called MetaGraph, that allows us to scalably index very large sets of DNA or protein sequences using annotated De Bruijn graphs. We demonstrate the feasibility of indexing the full extent of existing sequencing data and present new approaches for efficient and cost-effective full-text search at an on-demand cost of $0.10 per queried Mpb. We explore several practical use cases to mine existing archives for interesting associations and demonstrate the utility of our indexes for integrative analyses.

bioinformatics↗

bioRxiv2020

Dynamic analysis of sugar metabolism reveals the mechanisms of action of synthetic sugar analogs

Synthetic sugar analogs are widely applied in metabolic oligosaccharide engineering (MOE) and as novel drugs to interfere with glycoconjugate biosynthesis. However, mechanistic insights on their exact metabolism in the cell and over time are mostly lacking. We developed sensitive ion-pair UHPLC-QqQ mass spectrometry methodology for analysis of sugar metabolites in organisms and in model cells and identified novel low abundant nucleotide sugars in human cells, such as ADP-glucose and UDP-arabinose, and CMP-sialic acid (CMP-NeuNAc) in Drosophila. Dynamic tracing of propargyloxycarbonyl (Poc) labeled analogs, commonly used for MOE, revealed that ManNPoc is metabolized to both CMP-NeuNPoc and UDP-GlcNPoc. Finally, combined treatment of B16-F10 melanoma cells with antitumor compound 3Fax-NeuNAc and 13C-labeled GlcNAc revealed that endogenous CMP-NeuNAc levels started to decrease before a subsequent decrease of ManNAc 6-phosphate was observed. This implicates 3Fax-NeuNAc first acts as a substrate for cytosolic CMP-sialic acid synthetase and subsequently its product CMP-3Fax-NeuNAc functions as a feed-back inhibitor for UDP-GlcNAc 2-epimerase/N-acetylmannosamine kinase. Thus, dynamic analysis of sugar metabolites provides key insights into the time-dependent metabolism of synthetic sugars, which is important for the rational design of analogs with optimized effects.

biochemistry↗

bioRxiv2020

Deep learning-based molecular morphometrics for kidney biopsies

Morphologic examination of tissue biopsies is essential for histopathological diagnosis. However, accurate and scalable cellular quantification in human samples remains challenging. Here, we present a deep learning-based approach for antigen-specific cellular morphometrics in human kidney biopsies, which combines indirect immunofluorescence imaging with U-Net-based architectures for image-to-image translation and dual segmentation tasks, achieving human-level accuracy. In the kidney, podocyte loss represents a hallmark of glomerular injury and can be estimated in diagnostic biopsies. Thus, we profiled over 27,000 podocytes from 110 human samples, including patients with anti-neutrophil cytoplasmic antibody-associated glomerulonephritis (ANCA-GN), an immune-mediated disease with aggressive glomerular damage and irreversible loss of kidney function. Previously unknown morphometric signatures of podocyte depletion were identified in patients with ANCA-GN, which allowed patient classification and showed potential for risk stratification in combination with routine clinical tools. Together, our approach enables robust and scalable molecular morphometric analysis of human tissues, yielding deeper biological insights into the human kidney pathophysiology. SummaryDeep learning enables robust and scalable molecular morphometric analysis of human tissues, yielding deeper biological insights into the human kidney pathophysiology.

pathology↗

bioRxiv2019

A genetic map of the response to DNA damage in human cells

The response to DNA damage is critical for cellular homeostasis, tumor suppression, immunity and gametogenesis. In order to provide an unbiased and global view of the DNA damage response in human cells, we undertook 28 CRISPR/Cas9 screens against 25 genotoxic agents in the retinal pigment epithelium-1 (RPE1) cell line. These screens identified 840 genes whose loss causes either sensitivity or resistance to DNA damaging agents. Mining this dataset, we uncovered that ERCC6L2, which is mutated in a bone-marrow failure syndrome, codes for a canonical non-homologous end-joining pathway factor; that the RNA polymerase II component ELOF1 modulates the response to transcription-blocking agents and that the cytotoxicity of the G-quadruplex ligand pyridostatin involves trapping topoisomerase II on DNA. This map of the DNA damage response provides a rich resource to study this fundamental cellular system and has implications for the development and use of genotoxic agents in cancer therapy.

cancer biology↗

bioRxiv2019

Binding of the motor protein SecA to the bacterial protein translocation channel SecYEG in the absence of ATP

Translocation of many secretory proteins through the bacterial plasma membrane is facilitated by a complex of the SecYEG channel with the motor protein SecA. The ATP-free complex is unstable in detergent, raising the question how SecA may perform several rounds of ATP hydrolysis without being released from the membrane embedded SecYEG. Here we show that dual recognition of (i) SecYEG and (ii) vicinal acidic lipids confers an apparent nanomolar affinity. High-speed atomic force microscopy visualizes the complexes between monomeric SecA and SecYEG as being stable for tens of seconds. These long-lasting events and complementary shorter ones both give rise to single ion channel openings of equal duration. Furthermore, luminescence resonance energy transfer reveals two conformations of the SecYEG-SecA complex that differ in the protrusion depth of SecAs two-helix finger into SecYEGs aqueous channel. Such movement of the finger is in line with the power stroke mechanism of protein translocation.

biophysics↗

bioRxiv2019

Growth and rapid succession of methanotrophs effectively limit methane release during lake overturn

Lakes and reservoirs contribute substantially to atmospheric concentrations of the potent greenhouse gas methane. Lacustrine sediments produce large amounts of methane, which accumulate in oxygen-depleted hypolimnia of stratified lakes. Due to climate change and progressing eutrophication, the number of lakes with hypolimnetic methane storage may increase in the future. However, whether stored methane eventually reaches the atmosphere during lake overturn is a matter of controversy and depends critically on the response of the methanotroph assemblage. We show that the methanotroph assemblage in a mixing lake underwent both a substantial bloom and ecological succession. As a result, the methane oxidation capacity of the mixed layer kept pace with the methane supplied from the hypolimnion and most of the stored methane was oxidized. This previously unknown aspect of freshwater methanotroph ecology represents an effective mechanism limiting methane transfer from lakes to the atmosphere.

microbiology↗

bioRxiv2019

Lake overturn as a key driver for methane oxidation

Many seasonally stratified lakes accumulate substantial amounts of the greenhouse gas methane in the anoxic zone. Methane oxidizing bacteria in the water column act as a converter, oxidizing methane into carbon dioxide and biomass before it reaches the atmosphere. Current observations and estimates of this methane oxidation efficiency are diverging, especially for the lake overturn period. Here we combine a model of turbulent mixing, gas exchange and microbial growth with a comprehensive data set for autumn mixing to quantify the relevant physical and microbial processes. We show that the microbial methane converter is effectively transforming the increased methane flux during the overturn period. Only rare events of pronounced surface cooling in combination with persistently strong wind can trigger substantial outgassing. In the context of climate change, these results suggest that changes in the frequency of storms may be even more important for methane emissions from temperate lakes than gradual warming.

microbiology↗

bioRxiv2019

Ammonia inhibits energy metabolism in astrocytes in a rapid and glutamate dehydrogenase 2-dependent manner

In hepatic encephalopathy (HE) astrocyte dysfunction is a primary factor impairing neuronal activity under hyperammonemia. We show that mitochondria in cellular HE models undergo rapid fragmentation under hyperammonemia in a reversible manner. Mitochondrial respiration and glycolysis were instantaneously hampered in a pH-independent manner. A metabolomics approach revealed a subsequent accumulation of numerous amino acids, including branched chain amino acids, and glucose. N15 labeling of ammonia shows rapid incorporation of ammonia-derived nitrogen into glutamate and glutamate-derived amino acids. Downregulating human GLUD2, encoding mitochondrial glutamate dehydrogenase 2 (GDH2), inhibiting GDH2 activity by SIRT4 overexpression, and supplementing cells with glutamate or glutamine alleviated ammonia-induced inhibition of mitochondrial respiration. Thus, under hyperammonemic conditions, GDH2 catalyzes the removal of ammonia by reductive amination of -ketoglutarate but at the same time inhibits the TCA-cycle by depleting -ketoglutarate. Overall, we propose a mitochondria-dependent mechanism contributing to the early steps in the pathogenesis of HE where the interplay between energy metabolism and ammonia removal plays a pivotal role.

biochemistry↗

bioRxiv2019

Host metabolic reprogramming of Pseudomonas aeruginosa by phage-based quorum sensing modulation

The Pseudomonas quinolone signal (PQS) is a multifunctional quorum sensing molecule of key importance to the P. aeruginosa metabolism. We here describe that the lytic Pseudomonas bacterial virus LUZ19 targets this population-density-dependent signaling system by expressing quorum sensing-associated acyltransferase (Qst) during early infection. Qst interacts with a key biosynthesis pathway enzyme PqsD, resulting in decreased metabolites levels of PQS and its precursor 2-heptyl-4(1H)-quinolone. The lack of a functional PqsD enzyme impairs the normal LUZ19 infection but is restored by external supplementation of 2-heptyl-4(1H)-quinolone, showing that LUZ19 exploits PQS to successfully achieve its infection. A functional interaction network, which includes enzymes of the central carbon metabolism (CoaC/ThiD) and a novel non-ribosomal peptide synthetase pathway (PA1217), suggests a broader functional context for Qst, which blocks P. aeruginosa cell division. Qst represents an exquisite example of intricate reprogramming of the bacterium, which may be exploited towards antibiotic target discovery for this bacterial pathogen.

microbiology↗

bioRxiv2019

Model-based integration of genomics and metabolomics reveals SNP functionality in Mycobacterium tuberculosis

Human tuberculosis is caused by members of the Mycobacterium tuberculosis complex (MTBC) and presents variable disease outcomes. The variation has primarily been attributed to host and environmental factors, but recent evidence indicates an additional role of genetic diversity among MTBC clinical strains. Here, we used metabolomics to unravel the potential role of genetic variations in conferring strain-specific adaptive capacity and vulnerability. To systematically identify functionality of single nucleotide polymorphisms (SNPs), we developed a constraint-based approach that integrates metabolomic and genomic data. Model-based predictions were systematically tested against independent metabolome data; they correctly classified SNP effects in pyruvate kinase and suggested a genetic basis for strain-specific sensitivity to the antibiotic para-aminosalicylic acid. Our method is broadly applicable to mutations in enzyme-encoding genes across microbial life, opening new possibilities for identifying strain-specific metabolic vulnerabilities that could lead to more selective treatment strategies.

systems biology↗

bioRxiv2018

Two parallel pathways implement robust propionate catabolism and detoxification in mycobacteria

Tuberculosis remains a major global health threat with over 1.5 million deaths each year. Mycobacterium tuberculosis success story is related to a flexible metabolism, allowing growth despite restrictive conditions within the human host.\n\nHost lipids stores are a major carbon source in vivo. Their catabolism yields propionyl-CoA, which is processed by two parallel pathways, the methylmalonyl CoA pathway and the methylcitrate pathway. Both pathways are considered potential drug targets. The methylcitrate pathway is upregulated in the pathological context. However, intermediates of this pathway can be cytotoxic and Mtbs preference for its usage remains unclear.\n\nWe combine thermodynamic kinetic modeling, quantitative proteomics and time-resolved metabolomics to characterize the interplay between the two pathways and to show their functionalities in an efficient and fast propionate catabolism.\n\nWe find that the methylcitrate pathway acts as a transcriptionally regulated, high capacity catabolic pathway due to its favorable thermodynamics and metabolic control distribution. In contrast, the methylmalonyl pathway is constitutively fulfilling biosynthetic tasks and can quickly detoxify propionate pulses, but is thermodynamically restricted to lower capacity.

systems biology↗

bioRxiv2017

Identifying drug-gene interactions from CRISPR knockout screens with drugZ

Chemogenetic profiling enables the identification of gene mutations that enhance or suppress the activity of small molecules. This knowledge provides insights into drug mechanism-of-action, genetic vulnerabilities, and resistance mechanisms, all of which may help stratify patient populations. We present drugZ, an algorithm for identifying both synergistic and suppressor chemogenetic interactions from highly sensitive CRISPR screens, available at github.com/hart-lab/drugz. In screens for interactions with a poly(ADP-ribose) polymerase (PARP) inhibitor, DrugZ identifies a greater fraction of the homologous recombination repair pathway than contemporary methods, and confirms KEAP1 loss as a resistance factor for ERK inhibitors.

bioinformatics↗

bioRxiv2017

Antibodies set boundaries limiting microbial metabolite penetration and the resultant mammalian host response

Although the mammalian microbiota is well-contained within the intestine and on other body surfaces, it profoundly shapes development and metabolism of almost every host organ, presumably through pervasive microbial metabolite penetration. The challenge is that most metabolites can be of both host and microbial origin. We developed a model to distinguish between microbial and host metabolites by stable isotope tracing using fully 13C-labelled live non-replicating Escherichia coli, differentiating 12C and 13C isotopes with high-resolution mass spectrometry. Hundreds of microbial compounds penetrated across 23 host tissues and fluids after intestinal exposure: subsequent 12C host metabolome signatures included lipidemia, reduced glycolysis and inflammation. Mucosal barrier maturation with transient microbial exposure increased early clearance of penetrant bacterial metabolites from the small intestine into the urine, independently of antibody induction. Induced antibodies curtailed microbial metabolite exposure at the intestinal surface, by accelerating intestinal bacterial transit into the colon where metabolite transport mechanisms are limiting.

immunology↗