Genome‐wide screens have discovered a large set of essential genes in the opportunistic human pathogen Streptococcus pneumoniae. However, the functions of many essential genes are still unknown, hampering vaccine development and drug discovery. Based on results from transposon sequencing (Tn‐seq), we refined the list of essential genes in S. pneumoniae serotype 2 strain D39. Next, we created a knockdown library targeting 348 potentially essential genes by CRISPR interference (CRISPRi) and show a growth phenotype for 254 of them (73%). Using high‐content microscopy screening, we searched for essential genes of unknown function with clear phenotypes in cell morphology upon CRISPRi‐based depletion. We show that SPD_1416 and SPD_1417 (renamed to MurT and GatD, respectively) are essential for peptidoglycan synthesis, and that SPD_1198 and SPD_1197 (renamed to TarP and TarQ, respectively) are responsible for the polymerization of teichoic acid (TA) precursors. This knowledge enabled us to reconstruct the unique pneumococcal TA biosynthetic pathway. CRISPRi was also employed to unravel the role of the essential Clp‐proteolytic system in regulation of competence development, and we show that ClpX is the essential ATPase responsible for ClpP‐dependent repression of competence. The CRISPRi library provides a valuable tool for characterization of pneumococcal genes and pathways and revealed several promising antibiotic targets.

Streptococcus pneumoniae becomes competent for genetic transformation when exposed to an autoinducer peptide known as competence-stimulating peptide (CSP). This peptide was originally described as a quorum-sensing signal, enabling individual cells to regulate competence in response to population density. However, recent studies suggest that CSP may instead serve as a probe for sensing environmental cues, such as antibiotic stress or environmental diffusion. Here, we show that competence induction can be simultaneously influenced by cell density, external pH, antibiotic-induced stress, and cell history. Our experimental data is explained by a mathematical model where the environment and cell history modify the rate at which cells produce or sense CSP. Taken together, model and experiments indicate that autoinducer concentration can function as an indicator of cell density across environmental conditions, while also incorporating information on environmental factors or cell history, allowing cells to integrate cues such as antibiotic stress into their quorum-sensing response. This unifying perspective may apply to other debated quorum-sensing systems.

The structure and composition of bacterial communities can compromise antibiotic efficacy. For example, the secretion of β-lactamase by individual bacteria provides passive resistance for all residents within a polymicrobial environment. Here, we uncover that collective resistance can also develop via intracellular antibiotic deactivation. Real-time luminescence measurements and single-cell analysis demonstrate that the opportunistic human pathogen Streptococcus pneumoniae grows in medium supplemented with chloramphenicol (Cm) when resistant bacteria expressing Cm acetyltransferase (CAT) are present. We show that CAT processes Cm intracellularly but not extracellularly. In a mouse pneumonia model, more susceptible pneumococci survive Cm treatment when coinfected with a CAT-expressing strain. Mathematical modeling predicts that stable coexistence is only possible when antibiotic resistance comes at a fitness cost. Strikingly, CAT-expressing pneumococci in mouse lungs were outcompeted by susceptible cells even during Cm treatment. Our results highlight the importance of the microbial context during infectious disease as a potential complicating factor to antibiotic therapy.

The human pathogen Streptococcus pneumoniae (pneumococcus) is a bacterium that owes its success to complex gene expression regulation patterns on both the cellular and the population level. Expression of virulence factors enables a mostly hazard-free presence of the commensal, in balance with the host and niche competitors. Under specific circumstances, changes in this expression can result in a more aggressive behavior and the reversion to the invasive form as pathogen. These triggering conditions are very difficult to study due to the fact that environmental cues are often unknown or barely possible to simulate outside the host (in vitro). An alternative way of investigating expression patterns is found in synthetic biology approaches of reconstructing regulatory networks that mimic an observed behavior with orthogonal components. Here, we created a genetic platform suitable for synthetic biology approaches in S. pneumoniae and characterized a set of standardized promoters and reporters. We show that our system allows for fast and easy cloning with the BglBrick system and that reliable and robust gene expression after integration into the S. pneumoniae genome is achieved. In addition, the cloning system was extended to allow for direct linker-based assembly of ribosome binding sites, peptide tags, and fusion proteins, and we called this new generally applicable standard "BglFusion". The gene expression platform and the methods described in this study pave the way for employing synthetic biology approaches in S. pneumoniae.

Multistable gene regulatory systems sustain different levels of gene expression under identical external conditions. Such multistability is used to encode phenotypic states in processes including nutrient uptake and persistence in bacteria, fate selection in viral infection, cell-cycle control and development. Stochastic switching between different phenotypes can occur as the result of random fluctuations in molecular copy numbers of mRNA and proteins arising in transcription, translation, transport and binding. However, which component of a pathway triggers such a transition is generally not known. By linking single-cell experiments on the lactose-uptake pathway in E. coli to molecular simulations, we devise a general method to pinpoint the particular fluctuation driving phenotype switching and apply this method to the transition between the uninduced and induced states of the lac-genes. We find that the transition to the induced state is not caused only by the single event of lac-repressor unbinding, but depends crucially on the time period over which the repressor remains unbound from the lac-operon. We confirm this notion in strains with a high expression level of the lac-repressor (leading to shorter periods over which the lac-operon remains unbound), which show a reduced switching rate. Our techniques apply to multistable gene regulatory systems in general and allow to identify the molecular mechanisms behind stochastic transitions in gene regulatory circuits.