Targeted suppression of human IBD-associated gut microbiota commensals by phage consortia for treatment of intestinal inflammation.

Human gut commensals are increasingly suggested to impact non-communicable diseases, such as inflammatory bowel diseases (IBD), yet their targeted suppression remains a daunting unmet challenge. In four geographically distinct IBD cohorts (n = 537), we identify a clade of Klebsiella pneumoniae (Kp) strains, featuring a unique antibiotics resistance and mobilome signature, to be strongly associated with disease exacerbation and severity. Transfer of clinical IBD-associated Kp strains into colitis-prone, germ-free, and colonized mice enhances intestinal inflammation. Stepwise generation of a lytic five-phage combination, targeting sensitive and resistant IBD-associated Kp clade members through distinct mechanisms, enables effective Kp suppression in colitis-prone mice, driving an attenuated inflammation and disease severity. Proof-of-concept assessment of Kp-targeting phages in an artificial human gut and in healthy volunteers demonstrates gastric acid-dependent phage resilience, safety, and viability in the lower gut. Collectively, we demonstrate the feasibility of orally administered combination phage therapy in avoiding resistance, while effectively inhibiting non-communicable disease-contributing pathobionts.

Exodus: sequencing-based pipeline for quantification of pooled variants.

SUMMARY: Next-Generation Sequencing is widely used as a tool for identifying and quantifying microorganisms pooled together in either natural or designed samples. However, a prominent obstacle is achieving correct quantification when the pooled microbes are genetically related. In such cases, the outcome mostly depends on the method used for assigning reads to the individual targets. To address this challenge, we have developed Exodus-a reference-based Python algorithm for quantification of genomes, including those that are highly similar, when they are sequenced together in a single mix. To test Exodus' performance, we generated both empirical and in silico next-generation sequencing data of mixed genomes. When applying Exodus to these data, we observed median error rates varying between 0% and 0.21% as a function of the complexity of the mix. Importantly, no false negatives were recorded, demonstrating that Exodus' likelihood of missing an existing genome is very low, even if the genome's relative abundance is low and similar genomes are present in the same mix. Taken together, these data position Exodus as a reliable tool for identifying and quantifying genomes in mixed samples. Exodus is open source and free to use at: https://github.com/ilyavs/exodus. AVAILABILITY AND IMPLEMENTATION: Exodus is implemented in Python within a Snakemake framework. It is available on GitHub alongside a docker containing the required dependencies: https://github.com/ilyavs/exodus. The data underlying this article will be shared on reasonable request to the corresponding author. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prediction and large-scale analysis of primary operons in plastids reveals unique genetic features in the evolution of chloroplasts.

While bacterial operons have been thoroughly studied, few analyses of chloroplast operons exist, limiting the ability to study fundamental elements of these structures and utilize them for synthetic biology. Here, we describe the creation of a plastome-specific operon database (link provided below) achieved by combining experimental tools and predictive modeling. Using a Reverse-Transcription-PCR based method and published data, we determined the transcription-state of 213 gene pairs from four plastomes of evolutionary distinct organisms. By analyzing sequence-based features computed for our dataset, we were able to highlight fundamental characteristics differentiating between operon pairs and non-operon pairs. These include an interesting tendency toward maintaining similar messenger RNA-folding profiles in operon gene pairs, a feature that failed to yield any informative separation in cyanobacteria, suggesting that it catches unique traits of operon gene expression, which have evolved post-endosymbiosis. Subsequently, we used this feature set to train a random-forest classifier for operon prediction. As our results demonstrate the ability of our predictor to obtain accurate (84%) and robust predictions on unlabeled datasets, we proceeded to building operon maps for 2018 sequenced plastids. Our database may now present new opportunities for promoting metabolic engineering and synthetic biology in chloroplasts.

Solving the Riddle of the Evolution of Shine-Dalgarno Based Translation in Chloroplasts.

Chloroplasts originated from an ancient cyanobacterium and still harbor a bacterial-like genome. However, the centrality of Shine-Dalgarno ribosome binding, which predominantly regulates proteobacterial translation initiation, is significantly decreased in chloroplasts. As plastid ribosomal RNA anti-Shine-Dalgarno elements are similar to their bacterial counterparts, these sites alone cannot explain this decline. By computational simulation we show that upstream point mutations modulate the local structure of ribosomal RNA in chloroplasts, creating significantly tighter structures around the anti-Shine-Dalgarno locus, which in-turn reduce the probability of ribosome binding. To validate our model, we expressed two reporter genes (mCherry, hydrogenase) harboring a Shine-Dalgarno motif in the Chlamydomonas reinhardtii chloroplast. Coexpressing them with a 16S ribosomal RNA, modified according to our model, significantly enhances mCherry and hydrogenase expression compared with coexpression with an endogenous 16S gene.

ChimeraUGEM: unsupervised gene expression modeling in any given organism.

MOTIVATION: Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species. RESULTS: To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications. AVAILABILITY AND IMPLEMENTATION: Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Enhancing heterologous expression in Chlamydomonas reinhardtii by transcript sequence optimization.

Various species of microalgae have recently emerged as promising host-organisms for use in biotechnology industries due to their unique properties. These include efficient conversion of sunlight into organic compounds, the ability to grow in extreme conditions and the occurrence of numerous post-translational modification pathways. However, the inability to obtain high levels of nuclear heterologous gene expression in microalgae hinders the development of the entire field. To overcome this limitation, we analyzed different sequence optimization algorithms while studying the effect of transcript sequence features on heterologous expression in the model microalga Chlamydomonas reinhardtii, whose genome consists of rare features such as a high GC content. Based on the analysis of genomic data, we created eight unique sequences coding for a synthetic ferredoxin-hydrogenase enzyme, used here as a reporter gene. Following in silico design, these synthetic genes were transformed into the C. reinhardtii nucleus, after which gene expression levels were measured. The empirical data, measured in vivo show a discrepancy of up to 65-fold between the different constructs. In this work we demonstrate how the combination of computational methods and our empirical results enable us to learn about the way gene expression is encoded in the C. reinhardtii transcripts. We describe the deleterious effect on overall expression of codons encoding for splicing signals. Subsequently, our analysis shows that utilization of a frequent subset of preferred codons results in elevated transcript levels, and that mRNA folding energy in the vicinity of translation initiation significantly affects gene expression.

Binding of ferredoxin to algal photosystem I involves a single binding site and is composed of two thermodynamically distinct events.

Despite the impressive progress made in recent years in understanding the early steps in charge separation within the photosynthetic reaction centers, our knowledge of how ferredoxin (Fd) interacts with the acceptor side of photosystem I (PSI) is not as well developed. Fd accepts electrons after transiently docking to a binding site on the acceptor side of PSI. However, the exact location, as well as the stoichiometry, of this binding have been a matter of debate for more than two decades. Here, using Isothermal Titration Calorimetry (ITC) and purified components from wild type and mutant strains of the green algae Chlamydomonas reinhardtii we show that PSI has a single binding site for Fd, and that the association consists of two distinct binding events, each with a specific association constant.

Microoxic Niches within the Thylakoid Stroma of Air-Grown Chlamydomonas reinhardtii Protect [FeFe]-Hydrogenase and Support Hydrogen Production under Fully Aerobic Environment.

Photosynthetic hydrogen production in the microalga Chlamydomonas reinhardtii is catalyzed by two [FeFe]-hydrogenase isoforms, HydA1 and HydA2, both irreversibly inactivated upon a few seconds exposure to atmospheric oxygen. Until recently, it was thought that hydrogenase is not active in air-grown microalgal cells. In contrast, we show that the entire pool of cellular [FeFe]-hydrogenase remains active in air-grown cells due to efficient scavenging of oxygen. Using membrane inlet mass spectrometry, (18)O2 isotope, and various inhibitors, we were able to dissect the various oxygen uptake mechanisms. We found that both chlororespiration, catalyzed by plastid terminal oxidase, and Mehler reactions, catalyzed by photosystem I and Flavodiiron proteins, significantly contribute to oxygen uptake rate. This rate is considerably enhanced with increasing light, thus forming local anaerobic niches at the proximity of the stromal face of the thylakoid membrane. Furthermore, we found that in transition to high light, the hydrogen production rate is significantly enhanced for a short duration (100 s), thus indicating that [FeFe]-hydrogenase functions as an immediate sink for surplus electrons in aerobic as well as in anaerobic environments. In summary, we show that an anaerobic locality in the chloroplast preserves [FeFe]-hydrogenase activity and supports continuous hydrogen production in air-grown microalgal cells.

Bacteriophage therapy against pathological Klebsiella pneumoniae ameliorates the course of primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is characterized by progressive biliary inflammation and fibrosis. Although gut commensals are associated with PSC, their causative roles and therapeutic strategies remain elusive. Here we detect abundant Klebsiella pneumoniae (Kp) and Enterococcus gallinarum in fecal samples from 45 PSC patients, regardless of intestinal complications. Carriers of both pathogens exhibit high disease activity and poor clinical outcomes. Colonization of PSC-derived Kp in specific pathogen-free (SPF) hepatobiliary injury-prone mice enhances hepatic Th17 cell responses and exacerbates liver injury through bacterial translocation to mesenteric lymph nodes. We developed a lytic phage cocktail that targets PSC-derived Kp with a sustained suppressive effect in vitro. Oral administration of the phage cocktail lowers Kp levels in Kp-colonized germ-free mice and SPF mice, without off-target dysbiosis. Furthermore, we demonstrate that oral and intravenous phage administration successfully suppresses Kp levels and attenuates liver inflammation and disease severity in hepatobiliary injury-prone SPF mice. These results collectively suggest that using a lytic phage cocktail shows promise for targeting Kp in PSC.

Image-Processing Software for High-Throughput Quantification of Colony Luminescence.

Many microbiological assays include colonies that produce a luminescent or fluorescent (here generalized as "luminescent") signal, often in the form of luminescent halos around the colonies. These signals are used as reporters for a trait of interest; therefore, exact measurements of the luminescence are often desired. However, there is currently a lack of high-throughput methods for analyzing these assays, as common automatic image analysis tools are unsuitable for identifying these halos in the presence of the inherent biological noise. In this work, we have developed CFQuant-automatic, high-throughput software for the analysis of images from colony luminescence assays. CFQuant overcomes the problems of automatic identification by relying on the luminescence halo's expected shape and provides measurements of several features of the colonies and halos. We examined the performance of CFQuant using one such colony luminescence assay, where we achieved a high correlation (R = 0.85) between the measurements of CFQuant and known protein expression levels. This demonstrates CFQuant's potential as a fast and reliable tool for analysis of colony luminescence assays.IMPORTANCE Luminescent markers are widely used as reporters for various biologically interesting traits. In colony luminescence assays, the levels of luminescence around each colony can be used to compare the levels of traits of interest for different strains, treatments, etc., using quantitative measurements of the luminescence. However, automatic methods of obtaining this data are underdeveloped, making this a laborious manual process, especially in analyzing large numbers of colonies. The significance of this work is in developing an automatic, high-throughput tool for quantitative analysis of colony luminescence assays, which will allow fast collection of qualitative data from these assays and thus increase their overall usability.

The Integration of Multiple Nuclear-Encoded Transgenes in the Green Alga Chlamydomonas reinhardtii Results in Higher Transcription Levels.

The integration of genes into the nuclear genome of Chlamydomonas reinhardtii is mediated by Non-Homologous-End-Joining, thus resulting in unpredicted insertion locations. This phenomenon defines 'the position-effect', which is used to explain the variation of expression levels between different clones transformed with the same DNA fragment. Likewise, nuclear transgenes often undergo epigenetic silencing that reduces their expression; hence, nuclear transformations require high-throughput screening methods to isolate clones that express the foreign gene at a desirable level. Here, we show that the number of integration sites of heterologous genes results in higher mRNA levels. By transforming both a synthetic ferredoxin-hydrogenase fusion enzyme and a Gaussia-Luciferase reporter protein, we were able to obtain 33 positive clones that exhibit a wide range of synthetic expression. We then performed a droplet-digital polymerase-chain-reaction for these lines to measure their transgene DNA copy-number and mRNA levels. Surprisingly, most clones contain two integration sites of the synthetic gene (45.5%), whilst 33.3% contain one, 18.1% include three and 3.1% encompass four. Remarkably, we observed a positive correlation between the raw DNA copy-number values to the mRNA levels, suggesting a general effect of which transcription of transgenes is partially modulated by their number of copies in the genome. However, our data indicate that only clones harboring at least three copies of the target amplicon show a significant increment in mRNA levels of the reporter transgene. Lastly, we measured protein activity for each of the reporter genes to elucidate the effect of copy-number variation on heterologous expression.

The dual effect of a ferredoxin-hydrogenase fusion protein in vivo: successful divergence of the photosynthetic electron flux towards hydrogen production and elevated oxygen tolerance.

BACKGROUND: Hydrogen photo-production in green algae, catalyzed by the enzyme [FeFe]-hydrogenase (HydA), is considered a promising source of renewable clean energy. Yet, a significant increase in hydrogen production efficiency is necessary for industrial scale-up. We have previously shown that a major challenge to be resolved is the inferior competitiveness of HydA with NADPH production, catalyzed by ferredoxin-NADP(+)-reductase (FNR). In this work, we explored the in vivo hydrogen production efficiency of Fd-HydA, where the electron donor ferredoxin (Fd) is fused to HydA and expressed in the model organism Chlamydomonas reinhardtii. RESULTS: We show that once the Fd-HydA fusion gene is expressed in micro-algal cells of C. reinhardtii, the fusion enzyme is able to intercept photosynthetic electrons and use them for efficient hydrogen production, thus supporting the previous observations made in vitro. We found that Fd-HydA has a ~4.5-fold greater photosynthetic hydrogen production rate standardized for hydrogenase amount (PHPRH) than that of the native HydA in vivo. Furthermore, we provide evidence suggesting that the fusion protein is more resistant to oxygen than the native HydA. CONCLUSIONS: The in vivo photosynthetic activity of the Fd-HydA enzyme surpasses that of the native HydA and shows higher oxygen tolerance. Therefore, our results provide a solid platform for further engineering efforts towards efficient hydrogen production in microalgae through the expression of synthetic enzymes.