Biology subjects

Denereaz, J.

Publications and source records attributed to Denereaz, J..

6 recordsLinked to original sources

bioRxiv2026

Mechanistic basis of teichoic acid transport by a gatekeeper flippase

The cell wall is a complex structure that protects bacteria from environmental threats. Phosphocholine-containing teichoic acids are key cell wall biopolymers critical for host colonization, immune evasion, competence, and persistence in Streptococcus pneumoniae. The flippase TacF, a member of the multidrug/oligosaccharide-lipid/polysaccharide (MOP) superfamily, monitors the phosphocholine content of teichoic acids during transport, yet the underlying mechanism of this process remains unknown. We present a cryo-EM structure of S. pneumoniae TacF in lipid nanodiscs. In vivo complementation assays and molecular dynamics simulations reveal key residues involved in teichoic acid recognition and transport, while coevolutionary and conservation analyses delineate common mechanistic elements among MOP flippases, indicating a shared mechanism for polyprenyl-diphosphate-linked oligosaccharide lipid transport. Our findings provide mechanistic insights into an essential flippase involved in S. pneumoniae pathogenesis and a potential drug target.

biochemistry↗

bioRxiv2024

Dual CRISPRi-Seq for genome-wide genetic interaction studies identifies key genes involved in the pneumococcal cell cycle

A major goal in biology is to uncover the relationship between genotype and phenotype. However, identifying gene function is often hampered by genetic redundancy. For example, under standard laboratory conditions, three-quarters of the genes in the human pathogen Streptococcus pneumoniae are non-essential. A powerful approach to unravel genetic redundancy is by identifying gene-gene interactions. To uncover genetic interactions (GIs) in S. pneumoniae on a genome-wide scale, a generally applicable dual CRISPRi-Seq method and associated analysis pipeline was developed. Specifically, we created a library of 869 dual sgRNAs targeting high-confidence operons that encode essential and non-essential genes, covering over 70% of the genetic elements in the pneumococcal genome. Testing these 378,015 unique combinations, 4,026 significant GIs were identified, including 1,935 negative and 2,091 positive interactions. Besides known GIs, we found and confirmed previously unknown interactions involving genes responsible for fundamental cellular processes such as cell division, cell shape maintenance, and chromosome segregation. The presented methods and bioinformatic approaches can serve as a roadmap for genome-wide gene interaction studies in other organisms. Lastly, all interactions are available for exploration via the Pneumococcal Genetic Interaction Network (PneumoGIN) at https://veeninglab.shinyapps.io/PneumoGIN, which can serve as a starting point for new biological discoveries and translational research.

microbiology↗

bioRxiv2024

An unsupervised deep learning framework encodes super-resolved image features to decode bacterial cell cycle

Super-resolution microscopy can resolve cellular features at the nanoscale. However, increased spatial resolution comes with increased phototoxicity, and reduced temporal resolution. As a result, studies that require the highest spatial resolutions often rely on static or fixed images, lacking dynamic information. This is particularly true of bacteria, whose lateral dimensions approach the scale of the diffraction limit. In this work, we present Enso, a method based on unsupervised machine learning to recover bacterial cell cycle and cell type information from static single molecule localization microscopy (SMLM) images, whilst retaining nanoscale spatial resolution. Enso uses single-cell images as input, and orders cells according to their spatial pattern progression, ultimately linked to the cell cycle. Our method requires no a priori knowledge or categories, and is validated on both simulated and user-annotated experimental data.

bioinformatics↗

bioRxiv2023

A conserved antigen induces respiratory Th17-mediated serotype-independent protection against pneumococcal superinfection

Several vaccines targeting bacterial pathogens show reduced efficacy in the context of intercurrent viral infection indicating a new vaccinology approach is required to protect against such superinfections. To find antigens for the human pathogen Streptococcus pneumoniae that are effective following influenza infection, we performed CRISPRi-seq in a murine model of superinfection and identified the highly conserved lafB gene as virulence factor. We show that LafB is a membrane-associated, intracellular protein that catalyzes the formation of galactosyl-glucosyl-diacylglycerol, a glycolipid we show is important for cell wall homeostasis. Respiratory vaccination with recombinant LafB, in contrast to subcutaneous vaccination, was highly protective against all serotypes in a murine model. In contrast to standard pneumococcal capsule-based conjugate vaccines, protection did not require LafB-specific antibodies but was dependent on airway CD4+ T helper 17 cells. Healthy human individuals can elicit LafB-specific immune responses, suggesting its merit as a universal pneumococcal vaccine antigen that remains effective following influenza infection. One-Sentence SummaryDiscovery of a universal pneumococcal vaccine protective during superinfection.

microbiology↗

bioRxiv2023

CRISPRi-TnSeq: A genome-wide high-throughput tool for bacterial essential-nonessential genetic interaction mapping

Genetic interaction networks can help identify functional connections between genes and pathways, which can be leveraged to establish (new) gene function, drug targets, and fill pathway gaps. Since there is no optimal tool that can map genetic interactions across many different bacterial strains and species, we develop CRISPRi-TnSeq, a genome-wide tool that maps genetic interactions between essential genes and nonessential genes through the knockdown of a targeted essential gene (CRISPRi) and the simultaneous knockout of individual nonessential genes (Tn-Seq). CRISPRi-TnSeq thereby identifies, on a genome-wide scale, synthetic and suppressor-type relationships between essential and nonessential genes, enabling the construction of essential-nonessential genetic interaction networks. To develop and optimize CRISPRi-TnSeq, CRISPRi strains were obtained for 13 essential genes in Streptococcus pneumoniae, involved in different biological processes including metabolism, DNA replication, transcription, cell division and cell envelope synthesis. Transposon-mutant libraries were constructed in each strain enabling screening of [~]24,000 gene-gene pairs, which led to the identification of 1,334 genetic interactions, including 754 negative and 580 positive genetic interactions. Through extensive network analyses and validation experiments we identify a set of 17 pleiotropic genes, of which a subset tentatively functions as genetic capacitors, dampening phenotypic outcomes and protecting against perturbations. Furthermore, we focus on the relationships between cell wall synthesis, integrity and cell division and highlight: 1) how essential gene knockdown can be compensated by rerouting flux through nonessential genes in a pathway; 2) the existence of a delicate balance between Z-ring formation and localization, and septal and peripheral peptidoglycan (PG) synthesis to successfully accomplish cell division; 3) the control of c-di-AMP over intracellular K+ and turgor, and thereby modulation of the cell wall synthesis machinery; 4) the dynamic nature of cell wall protein CozEb and its effect on PG synthesis, cell shape morphology and envelope integrity; 5) functional dependency between chromosome decatenation and segregation, and the critical link with cell division, and cell wall synthesis. Overall, we show that CRISPRi-TnSeq uncovers genetic interactions between closely functionally linked genes and pathways, as well as disparate genes and pathways, highlighting pathway dependencies and valuable leads for gene function. Importantly, since both CRISPRi and Tn-Seq are widely used tools, CRISPRi-TnSeq should be relatively easy to implement to construct genetic interaction networks across many different microbial strains and species.

genetics↗

bioRxiv2021

Amoxicillin-resistant Streptococcus pneumoniae can be resensitized by targeting the mevalonate pathway as identified by sCRilecs-seq

Antibiotic resistance in the important opportunistic human pathogen Streptococcus pneumoniae is on the rise. This is particularly problematic in the case of the {beta}-lactam antibiotic amoxicillin, which is the first-line therapy. It is therefore crucial to uncover targets that would kill or resensitize amoxicillin-resistant pneumococci. To do so, we developed a genome-wide, single-cell based, gene silencing screen using CRISPR interference called sCRilecs-seq (subsets of CRISPR interference libraries extracted by fluorescence activated cell sorting coupled to next generation sequencing). Since amoxicillin affects growth and division, sCRilecs-seq was used to identify targets that are responsible for maintaining proper cell size. Our screen revealed that downregulation of the mevalonate pathway leads to extensive cell elongation. Further investigation into this phenotype indicates that it is caused by insufficient transport of cell wall precursors across the cell membrane due to a limitation in the production of undecaprenyl phosphate (Und-P), the lipid carrier responsible for this process. The data suggest that whereas peptidoglycan synthesis continues even with reduced Und-P levels, cell constriction is specifically halted. We successfully exploited this knowledge to create a combination treatment strategy where the FDA-approved drug clomiphene, an inhibitor of Und-P synthesis, is paired up with amoxicillin. Our results show that clomiphene potentiates the antimicrobial activity of amoxicillin and that combination therapy resensitizes amoxicillin-resistant S. pneumoniae. These findings could provide a starting point to develop a solution for the increasing amount of hard-to-treat amoxicillin-resistant pneumococcal infections.

microbiology↗