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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.

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.

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.

Fusobacterium nucleatum (FN) is enriched in human colorectal tumors [1] and its presence is correlated with poor prognosis [2]. Bacteriophages ("phages") are naturally occurring, self-amplifying viruses that are highly specific for particular bacterial species and strains and are recognized to have a high intrinsic safety. They offer a promising treatment strategy to both target FN associated with colorectal cancer (CRC) and, by phage engineering, to deliver an anti-tumoral immune-stimulating payload that may enhance the effectivity of other anti-cancer therapies such as checkpoint inhibitors in unresponsive colorectal cancer patients. The major challenge in engineering phages that target FN is the optimization of the eukaryotic payloads for high expression in this bacterial host. Since no data is available about codon usage and non-coding genetic sequences in the genome of FN bacteria, two computational approaches were used to optimize the codon usage for elevated payload expression of the first selected payload, murine IL-15. These approaches involved identifying ribosome binding sites and elongation speeds to optimize codon usage. Following design of an IL-15 expression vector, expression of this eukaryotic payload in FN bacteria was tested in vitro. For phage engineering, a plasmid containing the designed payload sequence was used to introduce the selected IL-15 encoding sequences into the phage genome. FN phage was successfully engineered to deliver a payload encoding the sequence of murine cytokine IL-15. Targeting of FN with engineered phage resulted in IL-15 protein expression in phage-infected bacteria in vitro. Given the specificity of FN for CRC tumors and the ability to locally express a eukaryotic protein by using FN targeting phage to deliver a payload, phage therapy may offer novel treatment approaches for patients with CRC. Citation Format: Lihi Ninio-Many, Yael Zigelman, Nufar Buchshtab, Yifat Elharar, Gal Eylon, Eliya Gidron, Dikla Berko-Ashur, Julian Nicenboim, Lior Zelcbuch, Einav Safyon Gartman, Sharon Kredo-Russo, Noga Kowalsman, Ilya Vainberg Slutskin, Iddo Weiner, Inbar Gahali-Sass, Naomi Zak, Sailaja Puttagunta, Merav Bassan. Novel engineering of therapeutic Fusobacterium nucleatum phage for colorectal cancer treatment [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P064.

The chloroplast, a photosynthetic organelle found in all plant and algae species, originates from an ancient event in which a cyanobacterium was engulfed by a larger eukaryote. Thus, modern chloroplasts still harbor a bacterial-like genome and carry out all stages of gene expression, including mRNA translation by a 70S ribosome. However, the Shine-Dalgarno model, which predominantly regulates translation initiation by base-pairing between the ribosomal RNA and the mRNA in model bacteria genera, was reported to have ambiguous effects on chloroplast gene expression. Here we show that while the Shine-Dalgarno motif is clearly conserved in proteobacterial mRNAs, its general absence from chloroplast mRNAs is observed in cyanobacteria as well, promoting the idea that the evolutionary process of reducing the centrality of the Shine-Dalgarno mechanism began well before plastid endosymbiosis. As plastid ribosomal RNA anti-Shine-Dalgarno elements are highly similar to their bacterial counterparts, these sites alone cannot explain the decline in plastid Shine-Dalgarno generality. However, 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 via the Shine-Dalgarno mechanism. To validate our model, we expressed a mCherry gene harboring a Shine-Dalgarno motif in the Chlamydomonas reinhardtii chloroplast. We show that co-expressing it with a 16S ribosomal RNA, modified according to our model, significantly enhances its expression compared to co-expression with an endogenous 16S gene.Significance statementChloroplasts are fascinating intracellular organelles which have evolved from an ancient cyanobacterium engulfed by a larger eukaryote. Surprisingly, the canonical mechanism regulating bacterial translation initiation – Shine-Dalgarno – has been shown to play a reduced role in chloroplasts. Here, we show that mutations upstream from the anti-Shine-Dalgarno element decrease the probability of spontaneous ribosome binding by modulating the secondary structure of the ribosomal RNA. These mutations constitute a regulatory step which acclimates the Shine-Dalgarno mechanism to the translational regulation regime of chloroplasts. Interestingly, we show that these chloroplast features occur in modern cyanobacteria as well, promoting the idea that they have evolved prior to endosymbiosis.

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.

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.

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., 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.

Background The prevalence of extended-spectrum beta-lactamase (ESBL) producing and carbapenem resistant (CR) Klebsiella pneumoniae (KP) has significantly risen in all geographic regions. Infections due to these bacteria are associated with high mortality across different infection types. Even with newer options, there remains an unmet need for safe and effective therapeutic options to treat infections caused by ESBL and CR KP. Phage therapy offers a novel approach with an unprecedented and orthogonal mechanism of action for treatment of diseases caused by pathogenic bacterial strains that are insufficiently addressed by available antibiotics. Phage-based therapies confer a high strain-level specificity and have a strong intrinsic safety profile. Here we describe the identification of novel phages that can effectively target antibiotic resistant KP strains. Host range of the 21 phages on 33 strain KP panel via solid culture infectivity assays. Red marks resistance to infection while sensitivity to phage is marked in green Methods KP clinical strains were isolated from human stool specimens preserved in glycerol. Selective culturing was carried, followed by testing of individual colonies for motility, indole and urease production, sequenced and analyzed by Kleborate tool to determine antibiotic resistant genes. Natural phages were isolated from plaques that developed on susceptible bacterial targets, sequenced and characterized. Results Antibiotic-resistant KP strains encoding beta lactamase genes or a carbapenemase (n=33) were isolated from healthy individuals (n=3), and patients with inflammatory bowel disease (n=26) or primary sclerosing cholangitis (n=3). Isolates sequencing revealed bla CTX-M15 and/or bla SHV encoding strains and carbapenamase KPC-2. A panel of 21 phages targeting the beta-lactamase- and carbapenemase-producing KP strains were identified. Phage sequencing revealed that all phages belong to the Caudovirales order and include 6 Siphoviridae, 14 Myoviridae, and 1 Podoviridae. In vitro lytic activity of the phages was tested on the isolated bacteria and revealed a coverage of 70% of the 33 isolated antibiotic resistant strains, >50% of which were targeted by multiple phages. Conclusion Collectively, these results demonstrate the feasibility of identifying phage with potent activity against antibiotic resistant KP strains, and may provide a novel therapeutic approach for treatment of ESBL and CR KP infections. Disclosures All Authors: No reported disclosures

Introduction: Recent studies demonstrate that bacterial species are present within the tumor microenvironment (Geller et al., 2017). The presence of F. nucleatum in tumors has been described to increase cancer cell proliferation, promote chemoresistance, and protect tumors against immune cell attack (Zhang et al., 2018). A higher abundance and prevalence of F. nucleatum has been associated with advanced tumor stage and poor prognosis in human colorectal carcinoma patients (Mima et al., 2016; Yan et al., 2017). Bacteriophages (“phages”) are viruses that specifically infect bacteria and play a critical role in regulating bacterial populations. Phages can be engineered to deliver therapeutic payloads (Schmidt, 2019). Reduction of intratumor F. nucleatum and targeted delivery of anticancer payloads to tumors using phages may offer novel approaches for localized cancer treatment. To date there are only a few reports identifying phages that target F. nucleatum (Zheng et al., 2019). Using an initially isolated phage, we have shown that these phages, administered intravenously, can reach tumor-associated F. nucleatum in vivo (Kahan-Hanum et al., 2019). The aim of the current study was to discover novel F. nucleatum-infecting phages that may serve to decrease intratumor F. nucleatum burden and/or deliver a localized payload for anticancer treatment. Methods: For phage isolation, human saliva samples were screened on lawns of F. nucleatum strains, and natural phages were isolated from plaques. Phage sequences were analyzed following sequencing in Illumina using Nextera kits and genome assembly using SPAde genome assembler. To characterize infectivity, double layer plaque assays on different hosts were carried out. Phage editing was carried out by new molecular tools for F. nucleatum that were developed internally. Results: Twelve novel phages were discovered, including phages against all 4 subspecies of F. nucleatum: animalis (n=2), vincentii (n=7), polymorphum (n=2), and nucleatum (n=1). Sequence analysis revealed that the phages differ greatly from one another and possess many unique features. Both temperate (lysogenic, n=4) and lytic (n=8) phages were isolated as determined by the presence of integrases required for lysogenic integration. Of the eight lytic phages, six share very little similarity with known phages or with each other. Moreover, two of the lytic phages are double-stranded lytic RNA phages, of which only eight have previously been reported. Editing of F. nucleatum-targeting phage by synthetic biology tools to introduce new sequences has already been carried out. Conclusions: The newly discovered unique phages against F. nucleatum offer the first step in development of a novel therapy targeting intratumor bacteria. Reduction of intratumoral F. nucleatum bacterial burden and/or delivery of anticancer or immune-stimulating payloads to colonic tumors associated with F. nucleatum may offer novel treatment approaches for patients with colorectal cancer. This abstract is also being presented as Poster B20. Citation Format: Lior Zelcbuch, Sagit Yahav, Nufar Buchshtab, Maya Kahan-Hanum, Ilya Vainberg-Slutskin, Iddo Weiner, Myriam Golembo, Sharon Kredo-Russo, Naomi Zak, Inbar Gahali-Sass, Sailaja Puttagunta, Merav Bassan. Novel phages targeting the intratumor-associated bacteria Fusobacterium nucleatum [abstract]. In: Proceedings of the AACR Special Conference on the Microbiome, Viruses, and Cancer; 2020 Feb 21-24; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2020;80(8 Suppl):Abstract nr PR07.

Algal chloroplasts are promising hosts for expression of heterologous proteins. In contrast to the nuclear genome, these organelles lack transgene silencing mechanisms, making them more susceptible to genetic manipulation. While it is well established that codon selection greatly affects heterologous expression, a chloroplast-specific software for application of different sequence optimization algorithms is still missing. In this work we built CSO - a graphical user interface allowing users to engineer their genes for chloroplast expression in the model microalga Chlamydomonas reinhardtii. Within the software, users can choose between three different powerful codon selection algorithms which were built specifically for chloroplast expression: Optimal codons and folding, ChimeraMap, and Mimic original host. To provide users with general intuition regarding the performance of these algorithms, we designed different mCherry reporter genes, using each of the software algorithms. We transformed and expressed each of them in the chloroplast of C. reinhardtii, and quantified protein and mRNA abundance, alongside overall growth rates. For the reporter tested here, Mimic original host yielded the best results, though it had a lower Codon Adaptation Index score; while the algorithm supporting the highest expression could change depending on the target gene, our observations show that matching the chloroplast codon usage bias alone does not necessarily maximize expression, and that optimizing more complex sequence features could prove beneficial. CSO is freely available online; a link to its installation and download page is given in Section 3.1.

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. Electronic supplementary material The online version of this article (doi:10.1186/s13068-016-0601-3) contains supplementary material, which is available to authorized users.