Global SLAM-seq for accurate mRNA decay determination and identification of NMD targets.

Gene expression analysis requires accurate measurements of global RNA degradation rates, earlier problematic with methods disruptive to cell physiology. Recently, metabolic RNA labeling emerged as an efficient and minimally invasive technique applied in mammalian cells. Here, we have adapted SH-linked alkylation for the metabolic sequencing of RNA (SLAM-seq) for a global mRNA stability study in yeast using 4-thiouracil pulse-chase labeling. We assign high-confidence half-life estimates for 67.5% of expressed ORFs, and measure a median half-life of 9.4 min. For mRNAs where half-life estimates exist in the literature, their ranking order was in good agreement with previous data, indicating that SLAM-seq efficiently classifies stable and unstable transcripts. We then leveraged our yeast protocol to identify targets of the nonsense-mediated decay (NMD) pathway by measuring the change in RNA half-lives, instead of steady-state RNA level changes. With SLAM-seq, we assign 580 transcripts as putative NMD targets, based on their measured half-lives in wild-type and upf3Δ mutants. We find 225 novel targets, and observe a strong agreement with previous reports of NMD targets, 61.2% of our candidates being identified in previous studies. This indicates that SLAM-seq is a simpler and more economic method for global quantification of mRNA half-lives. Our adaptation for yeast yielded global quantitative measures of the NMD effect on transcript half-lives, high correlation with RNA half-lives measured previously with more technically challenging protocols, and identification of novel NMD regulated transcripts that escaped prior detection.

A unique metabolic gene cluster regulates lactose and galactose metabolism in the yeast Candida intermedia.

Lactose assimilation is a relatively rare trait in yeasts, and Kluyveromyces yeast species have long served as model organisms for studying lactose metabolism. Meanwhile, the metabolic strategies of most other lactose-assimilating yeasts remain unknown. In this work, we have elucidated the genetic determinants of the superior lactose-growing yeast Candida intermedia. Through genomic and transcriptomic analyses, we identified three interdependent gene clusters responsible for the metabolism of lactose and its hydrolysis product galactose: the conserved LAC cluster (LAC12, LAC4) for lactose uptake and hydrolysis, the conserved GAL cluster (GAL1, GAL7, and GAL10) for galactose catabolism through the Leloir pathway, and a "GALLAC" cluster containing the transcriptional activator gene LAC9, second copies of GAL1 and GAL10, and a XYL1 gene encoding an aldose reductase involved in carbon overflow metabolism. Bioinformatic analysis suggests that the GALLAC cluster is unique to C. intermedia and has evolved through gene duplication and divergence, and deletion mutant phenotyping proved that the cluster is indispensable for C. intermedia's growth on lactose and galactose. We also show that the regulatory network in C. intermedia, governed by Lac9 and Gal1 from the GALLAC cluster, differs significantly from the galactose and lactose regulons in Saccharomyces cerevisiae, Kluyveromyces lactis, and Candida albicans. Moreover, although lactose and galactose metabolism are closely linked in C. intermedia, our results also point to important regulatory differences.IMPORTANCEThis study paves the way to a better understanding of lactose and galactose metabolism in the non-conventional yeast C. intermedia. Notably, the unique GALLAC cluster represents a new, interesting example of metabolic network rewiring and likely helps to explain how C. intermedia has evolved into an efficient lactose-assimilating yeast. With the Leloir pathway of budding yeasts acting like a model system for understanding the function, evolution, and regulation of eukaryotic metabolism, this work provides new evolutionary insights into yeast metabolic pathways and regulatory networks. In extension, the results will facilitate future development and use of C. intermedia as a cell-factory for conversion of lactose-rich whey into value-added products.

Detoxified synthetic bacterial membrane vesicles as a vaccine platform against bacteria and SARS-CoV-2.

The development of vaccines based on outer membrane vesicles (OMV) that naturally bud off from bacteria is an evolving field in infectious diseases. However, the inherent inflammatory nature of OMV limits their use as human vaccines. This study employed an engineered vesicle technology to develop synthetic bacterial vesicles (SyBV) that activate the immune system without the severe immunotoxicity of OMV. SyBV were generated from bacterial membranes through treatment with detergent and ionic stress. SyBV induced less inflammatory responses in macrophages and in mice compared to natural OMV. Immunization with SyBV or OMV induced comparable antigen-specific adaptive immunity. Specifically, immunization with Pseudomonas aeruginosa-derived SyBV protected mice against bacterial challenge, and this was accompanied by significant reduction in lung cell infiltration and inflammatory cytokines. Further, immunization with Escherichia coli-derived SyBV protected mice against E. coli sepsis, comparable to OMV-immunized group. The protective activity of SyBV was driven by the stimulation of B-cell and T-cell immunity. Also, SyBV were engineered to display the SARS-CoV-2 S1 protein on their surface, and these vesicles induced specific S1 protein antibody and T-cell responses. Collectively, these results demonstrate that SyBV may be a safe and efficient vaccine platform for the prevention of bacterial and viral infections.

Comparison of in situ sequence type analysis of Legionella pneumophila in respiratory tract secretions and environmental samples of a hospital in East Jerusalem.

Legionella pneumophila genotyping is important for epidemiological investigation of nosocomial and community-acquired outbreaks of legionellosis. The prevalence of legionellosis in pneumonia patients in the West Bank was monitored for the first time, and the sequence types (STs) from respiratory samples were compared with STs of environmental samples from different wards of the hospital. Sputum (n = 121) and bronchoalveolar lavage (BAL) (n = 74) specimens were cultured for L. pneumophila; genomic DNA was tested by 16S rRNA polymerase chain reaction (PCR) amplification. Nested PCR sequence-based typing (NPSBT) was implemented on DNA of the respiratory and environmental PCR-positive samples. Only one respiratory specimen was positive for L. pneumophila by culture. BAL gave a higher percentage of L. pneumophila-positive samples, 35% (26/74) than sputum, 15% (18/121) by PCR. NPSBT revealed the following STs: ST 1 (29%, 7/24), ST 461 (21%, 5/24), ST 1037 (4%, 1/24) from respiratory samples, STs from environmental samples: ST 1 (28.5%, 4/14), ST 187 (21.4%, 3/14) and ST 2070, ST 461, ST 1482 (7.1%, 1/14) each. This study emphasises the advantage of PCR over culture for the detection of L. pneumophila in countries where antibiotics are indiscriminately used prior to hospital admission. ST 1 was the predominant ST in both respiratory and environmental samples.

An automated positive selection screen in yeast provides support for boron-containing compounds as inhibitors of SARS-CoV-2 main protease.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus continues to cause severe disease and deaths in many parts of the world, despite massive vaccination efforts. Antiviral drugs to curb an ongoing infection remain a priority. The virus-encoded 3C-like main protease (MPro; nsp5) is seen as a promising target. Here, with a positive selection genetic system engineered in Saccharomyces cerevisiae using cleavage and release of MazF toxin as an indicator, we screened in a robotized setup small molecule libraries comprising ~2,500 compounds for MPro inhibitors. We detected eight compounds as effective against MPro expressed in yeast, five of which are characterized proteasome inhibitors. Molecular docking indicates that most of these bind covalently to the MPro catalytically active cysteine. Compounds were confirmed as MPro inhibitors in an in vitro enzymatic assay. Among those were three previously only predicted in silico; the boron-containing proteasome inhibitors bortezomib, delanzomib, and ixazomib. Importantly, we establish reaction conditions in vitro preserving the MPro-inhibitory activity of the boron-containing drugs. These differ from the standard conditions, which may explain why boron compounds have gone undetected in screens based on enzymatic in vitro assays. Our screening system is robust and can find inhibitors of a specific protease that are biostable, able to penetrate a cell membrane, and are not generally toxic. As a cellular assay, it can detect inhibitors that fail in a screen based on an in vitro enzymatic assay using standardized conditions, and now give support for boron compounds as MPro inhibitors. This method can also be adapted for other viral proteases.IMPORTANCEThe coronavirus disease 2019 (COVID-19) pandemic triggered the realization that we need flexible approaches to find treatments for emerging viral threats. We implemented a genetically engineered platform in yeast to detect inhibitors of the virus's main protease (MPro), a promising target to curb severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Screening molecule libraries, we identified candidate inhibitors and verified them in a biochemical assay. Moreover, the system detected boron-containing molecules as MPro inhibitors. Those were previously predicted computationally but never shown effective in a biochemical assay. Here, we demonstrate that they require a non-standard reaction buffer to function as MPro inhibitors. Hence, our cell-based method detects protease inhibitors missed by other approaches and provides support for the boron-containing molecules. We have thus demonstrated that our platform can screen large numbers of chemicals to find potential inhibitors of a viral protease. Importantly, the platform can be modified to detect protease targets from other emerging viruses.

A Genetic Trap in Yeast for Inhibitors of SARS-CoV-2 Main Protease.

The ongoing COVID-19 pandemic urges searches for antiviral agents that can block infection or ameliorate its symptoms. Using dissimilar search strategies for new antivirals will improve our overall chances of finding effective treatments. Here, we have established an experimental platform for screening of small molecule inhibitors of the SARS-CoV-2 main protease in Saccharomyces cerevisiae cells, genetically engineered to enhance cellular uptake of small molecules in the environment. The system consists of a fusion of the Escherichia coli toxin MazF and its antitoxin MazE, with insertion of a protease cleavage site in the linker peptide connecting the MazE and MazF moieties. Expression of the viral protease confers cleavage of the MazEF fusion, releasing the MazF toxin from its antitoxin, resulting in growth inhibition. In the presence of a small molecule inhibiting the protease, cleavage is blocked and the MazF toxin remains inhibited, promoting growth. The system thus allows positive selection for inhibitors. The engineered yeast strain is tagged with a fluorescent marker protein, allowing precise monitoring of its growth in the presence or absence of inhibitor. We detect an established main protease inhibitor by a robust growth increase, discernible down to 1 µM. The system is suitable for robotized large-scale screens. It allows in vivo evaluation of drug candidates and is rapidly adaptable for new variants of the protease with deviant site specificities. IMPORTANCE The COVID-19 pandemic may continue for several years before vaccination campaigns can put an end to it globally. Thus, the need for discovery of new antiviral drug candidates will remain. We have engineered a system in yeast cells for the detection of small molecule inhibitors of one attractive drug target of SARS-CoV-2, its main protease, which is required for viral replication. The ability to detect inhibitors in live cells brings the advantage that only compounds capable of entering the cell and remain stable there will score in the system. Moreover, because of its design in yeast cells, the system is rapidly adaptable for tuning the detection level and eventual modification of the protease cleavage site in the case of future mutant variants of the SARS-CoV-2 main protease or even for other proteases.

Biogeography and Environmental Drivers of Legionella pneumophila Abundance and Genotype Composition Across the West Bank: Relevance of a Genotype-Based Ecology for Understanding Legionella Occurrence.

The West Bank can be considered as a high-risk area for Legionella prevalence in drinking water due to high ambient temperature, intermittent water supply, frequent pressure loss, and storage of drinking water in roof containers. To assess occurrence of Legionella species, especially L. pneumophila, in the drinking water of the West Bank, the drinking water distribution systems of eight hospitals were sampled over a period of 2.3 years covering the seasonal cycle and the major geographic regions. To gain insight into potential environmental drivers, a set of physico-chemical and microbiological parameters was recorded. Sampling included drinking water and biofilm analyzed by culture and PCR-based methods. Cultivation led to the isolation of 180 strains of L. pneumophila that were genotyped by Multi-Locus Variable Number of Tandem Repeat Analysis (MLVA). Surprisingly, the abundance of culturable L. pneumophila was low in drinking water of the sampling sites, with only three out of eight sites where Legionella was observed at all (range: 30-500 CFU/liter). By contrast, biofilm and PCR-based analyses showed a higher prevalence. Statistical analyses with physico-chemical parameters revealed a decrease of L. pneumophila abundance for water and biofilm with increasing magnesium concentrations (>30 mg/l). MLVA-genotype analysis of the L. pneumophila isolates and their spatial distribution indicated three niches characterized by distinct physico-chemical parameters and inhabited by specific consortia of genotypes. This study provides novel insights into mechanisms shaping L. pneumophila populations and triggering their abundance leading to an understanding of their genotype-specific niches and ecology in support of improved prevention measures.

Characterization of Legionella pneumophila Populations by Multilocus Variable Number of Tandem Repeats (MLVA) Genotyping from Drinking Water and Biofilm in Hospitals from Different Regions of the West Bank.

The West Bank can be considered a high-risk area for Legionnaires' disease (LD) due to its hot climate, intermittent water supply and roof storage of drinking water. Legionella, mostly L. pneumophila, are responsible for LD, a severe, community-acquired and nosocomial pneumonia. To date, no extensive assessment of Legionella spp and L. pneumophila using cultivation in combination with molecular approaches in the West Bank has been published. Two years of environmental surveillance of Legionella in water and biofilms in the drinking water distribution systems (DWDS) of eight hospitals was carried out; 180 L. pneumophila strains were isolated, mostly from biofilms in DWDS. Most of the isolates were identified as serogroup (Sg) 1 (60%) and 6 (30%), while a minor fraction comprised Sg 8 and 10. Multilocus Variable number of tandem repeats Analysis using 13 loci (MLVA-8(12)) was applied as a high-resolution genotyping method and compared to the standard Sequence Based Typing (SBT). The isolates were genotyped in 27 MLVA-8(12) genotypes (Gt), comprising four MLVA clonal complexes (VACC 1; 2; 5; 11). The major fraction of isolates constituted Sequence Type (ST)1 and ST461. Most of the MLVA-genotypes were highly diverse and often unique. The MLVA-genotype composition showed substantial regional variability. In general, the applied MLVA-method made it possible to reproducibly genotype the isolates, and was consistent with SBT but showed a higher resolution. The advantage of the higher resolution was most evident for the subdivision of the large strain sets of ST1 and ST461; these STs were shown to be highly pneumonia-relevant in a former study. This shows that the resolution by MLVA is advantageous for back-tracking risk sites and for the avoidance of outbreaks of L. pneumophila. Overall, our results provide important insights into the detailed population structure of L. pneumophila, allowing for better risk assessment for DWDS.

A High-Throughput Method for Screening for Genes Controlling Bacterial Conjugation of Antibiotic Resistance.

The rapid horizontal transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. Plasmid-carrying donor strains are constructed in high-throughput. We then mix the resistance plasmid-carrying donors with recipients in a design where only transconjugants can reproduce, measure growth in dense intervals, and extract transmission times as the growth lag. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within Escherichia coli populations, by screening the Keio deletion collection in high replication. We recover all seven known chromosomal gene mutants affecting conjugation as donors and identify many novel mutants, all of which diminish antibiotic resistance transmission. We validate nine of the novel genes' effects in liquid mating assays and complement one of the novel genes' effect on conjugation (rseA). The new framework holds great potential for exhaustive disclosing of candidate targets for helper drugs that delay resistance development in patients and societies and improve the longevity of current and future antibiotics. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.IMPORTANCE The rapid transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within E. coli populations. We recover all previously known and many novel chromosomal gene mutants that affect conjugation efficiency. The new framework holds great potential for rapid screening of compounds that decrease transmission. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.