# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9079 | 0 | 0.9719 | Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes. Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth. | 2019 | 31749830 |
| 8259 | 1 | 0.9713 | Secondary Metabolite Transcriptomic Pipeline (SeMa-Trap), an expression-based exploration tool for increased secondary metabolite production in bacteria. For decades, natural products have been used as a primary resource in drug discovery pipelines to find new antibiotics, which are mainly produced as secondary metabolites by bacteria. The biosynthesis of these compounds is encoded in co-localized genes termed biosynthetic gene clusters (BGCs). However, BGCs are often not expressed under laboratory conditions. Several genetic manipulation strategies have been developed in order to activate or overexpress silent BGCs. Significant increases in production levels of secondary metabolites were indeed achieved by modifying the expression of genes encoding regulators and transporters, as well as genes involved in resistance or precursor biosynthesis. However, the abundance of genes encoding such functions within bacterial genomes requires prioritization of the most promising ones for genetic manipulation strategies. Here, we introduce the 'Secondary Metabolite Transcriptomic Pipeline' (SeMa-Trap), a user-friendly web-server, available at https://sema-trap.ziemertlab.com. SeMa-Trap facilitates RNA-Seq based transcriptome analyses, finds co-expression patterns between certain genes and BGCs of interest, and helps optimize the design of comparative transcriptomic analyses. Finally, SeMa-Trap provides interactive result pages for each BGC, allowing the easy exploration and comparison of expression patterns. In summary, SeMa-Trap allows a straightforward prioritization of genes that could be targeted via genetic engineering approaches to (over)express BGCs of interest. | 2022 | 35580059 |
| 9072 | 2 | 0.9711 | PanGeT: Pan-genomics tool. A decade after the concept of Pan-genome was first introduced; research in this field has spread its tentacles to areas such as pathogenesis of diseases, bacterial evolutionary studies and drug resistance. Gene content-based differentiation of virulent and a virulent strains of bacteria and identification of pathogen specific genes is imperative to understand their physiology and gain insights into the mechanism of genome evolution. Subsequently, this will aid in identifying diagnostic targets and in developing and selecting vaccines. The root of pan-genomic studies, however, is to identify the core genes, dispensable genes and strain specific genes across the genomes belonging to a clade. To this end, we have developed a tool, "PanGeT - Pan-genomics Tool" to compute the 'pan-genome' based on comparisons at the genome as well as the proteome levels. This automated tool is implemented using LaTeX libraries for effective visualization of overall pan-genome through graphical plots. Links to retrieve sequence information and functional annotations have also been provided. PanGeT can be downloaded from http://pranag.physics.iisc.ernet.in/PanGeT/ or https://github.com/PanGeTv1/PanGeT. | 2017 | 27851981 |
| 8135 | 3 | 0.9705 | Harnessing Genome Editing Techniques to Engineer Disease Resistance in Plants. Modern genome editing (GE) techniques, which include clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) system, transcription activator-like effector nucleases (TALENs), zinc-finger nucleases (ZFNs) and LAGLIDADG homing endonucleases (meganucleases), have so far been used for engineering disease resistance in crops. The use of GE technologies has grown very rapidly in recent years with numerous examples of targeted mutagenesis in crop plants, including gene knockouts, knockdowns, modifications, and the repression and activation of target genes. CRISPR/Cas9 supersedes all other GE techniques including TALENs and ZFNs for editing genes owing to its unprecedented efficiency, relative simplicity and low risk of off-target effects. Broad-spectrum disease resistance has been engineered in crops by GE of either specific host-susceptibility genes (S gene approach), or cleaving DNA of phytopathogens (bacteria, virus or fungi) to inhibit their proliferation. This review focuses on different GE techniques that can potentially be used to boost molecular immunity and resistance against different phytopathogens in crops, ultimately leading to the development of promising disease-resistant crop varieties. | 2019 | 31134108 |
| 9985 | 4 | 0.9703 | Identification of the First Gene Transfer Agent (GTA) Small Terminase in Rhodobacter capsulatus and Its Role in GTA Production and Packaging of DNA. Genetic exchange mediated by viruses of bacteria (bacteriophages) is the primary driver of rapid bacterial evolution. The priority of viruses is usually to propagate themselves. Most bacteriophages use the small terminase protein to identify their own genome and direct its inclusion into phage capsids. Gene transfer agents (GTAs) are descended from bacteriophages, but they instead package fragments of the entire bacterial genome without preference for their own genes. GTAs do not selectively target specific DNA, and no GTA small terminases are known. Here, we identified the small terminase from the model Rhodobacter capsulatus GTA, which then allowed prediction of analogues in other species. We examined the role of the small terminase in GTA production and propose a structural basis for random DNA packaging.IMPORTANCE Random transfer of any and all genes between bacteria could be influential in the spread of virulence or antimicrobial resistance genes. Discovery of the true prevalence of GTAs in sequenced genomes is hampered by their apparent similarity to bacteriophages. Our data allowed the prediction of small terminases in diverse GTA producer species, and defining the characteristics of a "GTA-type" terminase could be an important step toward novel GTA identification. Importantly, the GTA small terminase shares many features with its phage counterpart. We propose that the GTA terminase complex could become a streamlined model system to answer fundamental questions about double-stranded DNA (dsDNA) packaging by viruses that have not been forthcoming to date. | 2019 | 31534034 |
| 9076 | 5 | 0.9702 | ResiDB: An automated database manager for sequence data. The amount of publicly available DNA sequence data is drastically increasing, making it a tedious task to create sequence databases necessary for the design of diagnostic assays. The selection of appropriate sequences is especially challenging in genes affected by frequent point mutations such as antibiotic resistance genes. To overcome this issue, we have designed the webtool resiDB, a rapid and user-friendly sequence database manager for bacteria, fungi, viruses, protozoa, invertebrates, plants, archaea, environmental and whole genome shotgun sequence data. It automatically identifies and curates sequence clusters to create custom sequence databases based on user-defined input sequences. A collection of helpful visualization tools gives the user the opportunity to easily access, evaluate, edit, and download the newly created database. Consequently, researchers do no longer have to manually manage sequence data retrieval, deal with hardware limitations, and run multiple independent software tools, each having its own requirements, input and output formats. Our tool was developed within the H2020 project FAPIC aiming to develop a single diagnostic assay targeting all sepsis-relevant pathogens and antibiotic resistance mechanisms. ResiDB is freely accessible to all users through https://residb.ait.ac.at/. | 2021 | 33495705 |
| 8398 | 6 | 0.9701 | ARTS 2.0: feature updates and expansion of the Antibiotic Resistant Target Seeker for comparative genome mining. Multi-drug resistant pathogens have become a major threat to human health and new antibiotics are urgently needed. Most antibiotics are derived from secondary metabolites produced by bacteria. In order to avoid suicide, these bacteria usually encode resistance genes, in some cases within the biosynthetic gene cluster (BGC) of the respective antibiotic compound. Modern genome mining tools enable researchers to computationally detect and predict BGCs that encode the biosynthesis of secondary metabolites. The major challenge now is the prioritization of the most promising BGCs encoding antibiotics with novel modes of action. A recently developed target-directed genome mining approach allows researchers to predict the mode of action of the encoded compound of an uncharacterized BGC based on the presence of resistant target genes. In 2017, we introduced the 'Antibiotic Resistant Target Seeker' (ARTS). ARTS allows for specific and efficient genome mining for antibiotics with interesting and novel targets by rapidly linking housekeeping and known resistance genes to BGC proximity, duplication and horizontal gene transfer (HGT) events. Here, we present ARTS 2.0 available at http://arts.ziemertlab.com. ARTS 2.0 now includes options for automated target directed genome mining in all bacterial taxa as well as metagenomic data. Furthermore, it enables comparison of similar BGCs from different genomes and their putative resistance genes. | 2020 | 32427317 |
| 8263 | 7 | 0.9699 | CRISPR/Cas9: A Novel Weapon in the Arsenal to Combat Plant Diseases. Plant pathogens like virus, bacteria, and fungi incur a huge loss of global productivity. Targeting the dominant R gene resulted in the evolution of resistance in pathogens, which shifted plant pathologists' attention toward host susceptibility factors (or S genes). Herein, the application of sequence-specific nucleases (SSNs) for targeted genome editing are gaining more importance, which utilize the use of meganucleases (MN), zinc finger nucleases (ZFNs), transcription activator-like effector-based nucleases (TALEN) with the latest one namely clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9). The first generation of genome editing technologies, due to their cumbersome nature, is becoming obsolete. Owing to its simple and inexpensive nature the use of CRISPR/Cas9 system has revolutionized targeted genome editing technology. CRISPR/Cas9 system has been exploited for developing resistance against virus, bacteria, and fungi. For resistance to DNA viruses (mainly single-stranded DNA viruses), different parts of the viral genome have been targeted transiently and by the development of transgenic plants. For RNA viruses, mainly the host susceptibility factors and very recently the viral RNA genome itself have been targeted. Fungal and bacterial resistance has been achieved mainly by targeting the host susceptibility genes through the development of transgenics. In spite of these successes CRISPR/Cas9 system suffers from off-targeting. This and other problems associated with this system are being tackled by the continuous discovery/evolution of new variants. Finally, the regulatory standpoint regarding CRISPR/Cas9 will determine the fate of using this versatile tool in developing pathogen resistance in crop plants. | 2018 | 30697226 |
| 8155 | 8 | 0.9698 | Gut bacteria enable prostate cancer growth. Testosterone-synthetizing gut bacteria drive resistance to therapy. | 2021 | 34618567 |
| 9073 | 9 | 0.9698 | EpitoCore: Mining Conserved Epitope Vaccine Candidates in the Core Proteome of Multiple Bacteria Strains. In reverse vaccinology approaches, complete proteomes of bacteria are submitted to multiple computational prediction steps in order to filter proteins that are possible vaccine candidates. Most available tools perform such analysis only in a single strain, or a very limited number of strains. But the vast amount of genomic data had shown that most bacteria contain pangenomes, i.e., their genomic information contains core, conserved genes, and random accessory genes specific to each strain. Therefore, in reverse vaccinology methods it is of the utmost importance to define core proteins and core epitopes. EpitoCore is a decision-tree pipeline developed to fulfill that need. It provides surfaceome prediction of proteins from related strains, defines core proteins within those, calculate their immunogenicity, predicts epitopes for a given set of MHC alleles defined by the user, and then reports if epitopes are located extracellularly and if they are conserved among the core homologs. Pipeline performance is illustrated by mining peptide vaccine candidates in Mycobacterium avium hominissuis strains. From a total proteome of ~4,800 proteins per strain, EpitoCore predicted 103 highly immunogenic core homologs located at cell surface, many of those related to virulence and drug resistance. Conserved epitopes identified among these homologs allows the users to define sets of peptides with potential to immunize the largest coverage of tested HLA alleles using peptide-based vaccines. Therefore, EpitoCore is able to provide automated identification of conserved epitopes in bacterial pangenomic datasets. | 2020 | 32431712 |
| 8161 | 10 | 0.9697 | Integrative strategies against multidrug-resistant bacteria: Synthesizing novel antimicrobial frontiers for global health. Concerningly, multidrug-resistant bacteria have emerged as a prime worldwide trouble, obstructing the treatment of infectious diseases and causing doubts about the therapeutic accidentalness of presently existing drugs. Novel antimicrobial interventions deserve development as conventional antibiotics are incapable of keeping pace with bacteria evolution. Various promising approaches to combat MDR infections are discussed in this review. Antimicrobial peptides are examined for their broad-spectrum efficacy and reduced ability to develop resistance, while phage therapy may be used under extreme situations when antibiotics fail. In addition, the possibility of CRISPR-Cas systems for specifically targeting and eradicating resistance genes from bacterial populations will be explored. Nanotechnology has opened up the route to improve the delivery system of the drug itself, increasing the efficacy and specificity of antimicrobial action while protecting its host. Discovering potential antimicrobial agents is an exciting prospect through developments in synthetic biology and the rediscovery of natural product-based medicines. Moreover, host-directed therapies are now becoming popular as an adjunct to the main strategies of therapeutics without specifically targeting pathogens. Although these developments appear impressive, questions about production scaling, regulatory approvals, safety, and efficacy for clinical employment still loom large. Thus, tackling the MDR burden requires a multi-pronged plan, integrating newer treatment modalities with existing antibiotic regimens, enforcing robust stewardship initiatives, and effecting policy changes at the global level. The international health community can gird itself against the growing menace of antibiotic resistance if collaboration between interdisciplinary bodies and sustained research endeavours is encouraged. In this study, we evaluate the synergistic potential of combining various medicines in addition to summarizing recent advancements. To rethink antimicrobial stewardship in the future, we provide a multi-tiered paradigm that combines pathogen-focused and host-directed strategies. | 2025 | 40914328 |
| 9219 | 11 | 0.9697 | Knowing and Naming: Phage Annotation and Nomenclature for Phage Therapy. Bacteriophages, or phages, are viruses that infect bacteria shaping microbial communities and ecosystems. They have gained attention as potential agents against antibiotic resistance. In phage therapy, lytic phages are preferred for their bacteria killing ability, while temperate phages, which can transfer antibiotic resistance or toxin genes, are avoided. Selection relies on plaque morphology and genome sequencing. This review outlines annotating genomes, identifying critical genomic features, and assigning functional labels to protein-coding sequences. These annotations prevent the transfer of unwanted genes, such as antimicrobial resistance or toxin genes, during phage therapy. Additionally, it covers International Committee on Taxonomy of Viruses (ICTV)-an established phage nomenclature system for simplified classification and communication. Accurate phage genome annotation and nomenclature provide insights into phage-host interactions, replication strategies, and evolution, accelerating our understanding of the diversity and evolution of phages and facilitating the development of phage-based therapies. | 2023 | 37932119 |
| 9179 | 12 | 0.9697 | A detailed landscape of CRISPR-Cas-mediated plant disease and pest management. Genome editing technology has rapidly evolved to knock-out genes, create targeted genetic variation, install precise insertion/deletion and single nucleotide changes, and perform large-scale alteration. The flexible and multipurpose editing technologies have started playing a substantial role in the field of plant disease management. CRISPR-Cas has reduced many limitations of earlier technologies and emerged as a versatile toolbox for genome manipulation. This review summarizes the phenomenal progress of the use of the CRISPR toolkit in the field of plant pathology. CRISPR-Cas toolbox aids in the basic studies on host-pathogen interaction, in identifying virulence genes in pathogens, deciphering resistance and susceptibility factors in host plants, and engineering host genome for developing resistance. We extensively reviewed the successful genome editing applications for host plant resistance against a wide range of biotic factors, including viruses, fungi, oomycetes, bacteria, nematodes, insect pests, and parasitic plants. Recent use of CRISPR-Cas gene drive to suppress the population of pathogens and pests has also been discussed. Furthermore, we highlight exciting new uses of the CRISPR-Cas system as diagnostic tools, which rapidly detect pathogenic microorganism. This comprehensive yet concise review discusses innumerable strategies to reduce the burden of crop protection. | 2022 | 35835393 |
| 8136 | 13 | 0.9697 | Recent progress in CRISPR/Cas9-based genome editing for enhancing plant disease resistance. Nowadays, agricultural production is strongly affected by both climate change and pathogen attacks which seriously threaten global food security. For a long time, researchers have been waiting for a tool allowing DNA/RNA manipulation to tailor genes and their expression. Some earlier genetic manipulation methods such as meganucleases (MNs), zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) allowed site directed modification but their successful rate was limited due to lack of flexibility when targeting a 'site-specific nucleic acid'. The discovery of clustered regularly interspaced short palindrome repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system has revolutionized genome editing domain in different living organisms during the past 9 years. Based on RNA-guided DNA/RNA recognition, CRISPR/Cas9 optimizations have offered an unrecorded scientific opportunity to engineer plants resistant to diverse pathogens. In this report, we describe the main characteristics of the primary reported-genome editing tools ((MNs, ZFNs, TALENs) and evaluate the different CRISPR/Cas9 methods and achievements in developing crop plants resistant to viruses, fungi and bacteria. | 2023 | 36871676 |
| 8264 | 14 | 0.9695 | Anti-CRISPR Phages Cooperate to Overcome CRISPR-Cas Immunity. Some phages encode anti-CRISPR (acr) genes, which antagonize bacterial CRISPR-Cas immune systems by binding components of its machinery, but it is less clear how deployment of these acr genes impacts phage replication and epidemiology. Here, we demonstrate that bacteria with CRISPR-Cas resistance are still partially immune to Acr-encoding phage. As a consequence, Acr-phages often need to cooperate in order to overcome CRISPR resistance, with a first phage blocking the host CRISPR-Cas immune system to allow a second Acr-phage to successfully replicate. This cooperation leads to epidemiological tipping points in which the initial density of Acr-phage tips the balance from phage extinction to a phage epidemic. Furthermore, both higher levels of CRISPR-Cas immunity and weaker Acr activities shift the tipping points toward higher initial phage densities. Collectively, these data help elucidate how interactions between phage-encoded immune suppressors and the CRISPR systems they target shape bacteria-phage population dynamics. | 2018 | 30033365 |
| 8424 | 15 | 0.9695 | Postseptational chromosome partitioning in bacteria. Mutations in the spoIIIE gene prevent proper partitioning of one chromosome into the developing prespore during sporulation but have no overt effect on partitioning in vegetatively dividing cells. However, the expression of spoIIIE in vegetative cells and the occurrence of genes closely related to spoIIIE in a range of nonsporulating eubacteria suggested a more general function for the protein. Here we show that SpoIIIE protein is needed for optimal chromosome partitioning in vegetative cells of Bacillus subtilis when the normal tight coordination between septation and nucleoid partitioning is perturbed or when septum positioning is altered. A functional SpoIIIE protein allows cells to recover from a state in which their chromosome has been trapped by a closing septum. By analogy to its function during sporulation, we suggest that SpoIIIE facilitates partitioning by actively translocating the chromosome out of the septum. In addition to enhancing the fidelity of nucleoid partitioning, SpoIIIE also seems to be required for maximal resistance to antibiotics that interfere with DNA metabolism. The results have important implications for our understanding of the functions of genes involved in the primary partitioning machinery in bacteria and of how septum placement is controlled. | 1995 | 7567988 |
| 9078 | 16 | 0.9695 | MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota. MOTIVATION: Antibiotic resistance is an important global public health problem. Human gut microbiota is an accumulator of resistance genes potentially providing them to pathogens. It is important to develop tools for identifying the mechanisms of how resistance is transmitted between gut microbial species and pathogens. RESULTS: We developed MetaCherchant-an algorithm for extracting the genomic environment of antibiotic resistance genes from metagenomic data in the form of a graph. The algorithm was validated on a number of simulated and published datasets, as well as applied to new 'shotgun' metagenomes of gut microbiota from patients with Helicobacter pylori who underwent antibiotic therapy. Genomic context was reconstructed for several major resistance genes. Taxonomic annotation of the context suggests that within a single metagenome, the resistance genes can be contained in genomes of multiple species. MetaCherchant allows reconstruction of mobile elements with resistance genes within the genomes of bacteria using metagenomic data. Application of MetaCherchant in differential mode produced specific graph structures suggesting the evidence of possible resistance gene transmission within a mobile element that occurred as a result of the antibiotic therapy. MetaCherchant is a promising tool giving researchers an opportunity to get an insight into dynamics of resistance transmission in vivo basing on metagenomic data. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available for download at https://github.com/ctlab/metacherchant. The code is written in Java and is platform-independent. COTANCT: ulyantsev@rain.ifmo.ru. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. | 2018 | 29092015 |
| 9083 | 17 | 0.9694 | ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences. BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract. | 2024 | 38725076 |
| 8265 | 18 | 0.9692 | Mathematical modelling of CRISPR-Cas system effects on biofilm formation. Clustered regularly interspaced short palindromic repeats (CRISPR), linked with CRISPR associated (Cas) genes, can confer adaptive immunity to bacteria, against bacteriophage infections. Thus from a therapeutic standpoint, CRISPR immunity increases biofilm resistance to phage therapy. Recently, however, CRISPR-Cas genes have been implicated in reducing biofilm formation in lysogenized cells. Thus CRISPR immunity can have complex effects on phage-host-lysogen interactions, particularly in a biofilm. In this contribution, we develop and analyse a series of dynamical systems to elucidate and disentangle these interactions. Two competition models are used to study the effects of lysogens (first model) and CRISPR-immune bacteria (second model) in the biofilm. In the third model, the effect of delivering lysogens to a CRISPR-immune biofilm is investigated. Using standard analyses of equilibria, stability and bifurcations, our models predict that lysogens may be able to displace CRISPR-immune bacteria in a biofilm, and thus suggest strategies to eliminate phage-resistant biofilms. | 2017 | 28426329 |
| 9060 | 19 | 0.9692 | Targetable nano-delivery vehicles to deliver anti-bacterial small acid-soluble spore protein (SASP) genes. Interest in phage-based therapeutics is increasing, at least in part due to the need for new treatment options for infections caused by antibiotic-resistant bacteria. It is possible to use wild-type (WT) phages to treat bacterial infections, but it is also possible to modify WT phages to generate therapeutics with improved features. Here, we will discuss features of Phico Therapeutics' SASPject technology, which modifies phages for use as targetable nano-delivery vehicles (NDV), to introduce antibacterial Small Acid Soluble Spore Protein (SASP) genes into specific target bacteria. | 2021 | 34723318 |