Article
Genetics & Heredity
Saniya Patil, Aseem Palande, Tejan Lodhiya, Awadhesh Pandit, Raju Mukherjee
Summary: Sequencing transposon mutant libraries have been crucial in identifying essential and non-essential genes in bacteria, particularly important for Mycobacterium tuberculosis with many unknown functions in its genome. Fluctuations in insertion frequencies across different genes were observed during growth in nutrient-replete conditions, indicating novel modes of adaptation by mutants. The study also revealed changes in essentiality status of genetic features, providing new insights into bacterial adaptation mechanisms.
Article
Microbiology
Delphine Lariviere, Laura Wickham, Kenneth Keiler, Anton Nekrutenko
Summary: Our work provides an assessment of the currently available tools for TIS data analysis. It offers ready-to-use workflows that can be invoked by anyone in the world using our public Galaxy platform. To lower the entry barriers, we have also developed interactive tutorials explaining details of TIS data analysis procedures.
Article
Microbiology
Keith Levendosky, Niklas Janisch, Luis E. N. Quadri
Summary: Mk is a common nontuberculous mycobacterial pathogen associated with tuberculosis-like pulmonary disease. Drug resistance emergence poses a threat to the control of Mk infections that require long-term multidrug treatment. A comprehensive understanding of Mk biology is crucial for the development of new and more effective therapeutics. Through transposon-based mutagenesis and analysis of insertion site identification data, we identified genes and genomic regions essential for Mk growth. Comparative genomics analysis highlighted similarities and differences between Mk and other mycobacteria. This information can aid in identifying potential Mk drug targets and guiding future studies on Mk biology.
Article
Veterinary Sciences
Amanda J. Gibson, Ian J. Passmore, Valwynne Faulkner, Dong Xia, Irene Nobeli, Jennifer Stiens, Sam Willcocks, Taane G. Clark, Ben Sobkowiak, Dirk Werling, Bernardo Villarreal-Ramos, Brendan W. Wren, Sharon L. Kendall
Summary: The study investigated the differences in gene essentiality between Mycobacterium bovis and Mycobacterium tuberculosis using transposon libraries and CRISPRi. It found shared essential genes between the two species, as well as species-specific responses to gene silencing. The research suggests potential differences in target vulnerability in antimicrobial pathways between human and animal adapted lineages of MTBC.
FRONTIERS IN VETERINARY SCIENCE
(2021)
Article
Microbiology
Allison F. Carey, Xin Wang, Nico Cicchetti, Caitlin N. Spaulding, Qingyun Liu, Forrest Hopkins, Jessica Brown, Jaimie Sixsmith, Rujapak Sutiwisesak, Samuel M. Behar, Thomas R. Ioerger, Sarah M. Fortune
Summary: There is evidence that genetic diversity in Mycobacterium tuberculosis affects infection outcomes and vaccination. Strains belonging to the mL2 sublineage of M. tuberculosis are associated with clinical features such as hypervirulence, treatment failure, and vaccine escape. These strains show distinct growth dynamics and vaccine resistance, which can be attributed to adaptive genetic changes in stress and host response pathways.
Article
Microbiology
Dalin Rifat, Liang Chen, Barry N. Kreiswirth, Eric L. Nuermberger
Summary: Using transposon mutagenesis and deep sequencing, this study comprehensively analyzed essential genes in M. abscessus and found that most of them have homology with essential genes in M. tuberculosis, providing valuable insights for understanding M. abscessus pathogenicity and drug development.
Article
Biology
Chidiebere Akusobi, Bouchra S. Benghomari, Junhao Zhu, Ian D. Wolf, Shreya Singhvi, Charles L. Dulberger, Thomas R. Ioerger, Eric J. Rubin, Bavesh D. Kana
Summary: This study identified essential genes in Mab and characterized the role of PBP-lipo in cell wall synthesis. Inhibition of PBP-lipo could increase the susceptibility of Mab to various antibiotics, making it a potential drug target for treating Mab infections.
Article
Microbiology
Sanjeevani Choudhery, A. Jacob Brown, Chidiebere Akusobi, Eric J. Rubin, Christopher M. Sassetti, Thomas R. Ioerger
Summary: The study found that there are site-specific biases affecting the frequency of insertion of the Himar1 transposon at different TA sites. By developing a quantitative model based on patterns in the nucleotides surrounding TA sites, it is possible to predict expected counts at each site and improve estimates of gene fitness effects. The TTN-Fitness method allows for finer distinctions among essential and nonessential genes by comparing observed and expected counts based on insertion preferences.
Article
Mathematical & Computational Biology
Meilin Jiang, Seonjoo Lee, A. James O'Malley, Yaakov Stern, Zhigang Li
Summary: Mediation analyses are important for causal inference in biomedical research, but little attention has been paid to mediators with zero-inflated structures. We propose a novel mediation modeling approach that can decompose the total mediation effect into two components induced by zero-inflated structures. Extensive simulations and a real study demonstrate the superior performance of our approach compared to existing methods.
STATISTICS IN MEDICINE
(2023)
Article
Biochemical Research Methods
Tao Cui, Tingting Wang
Summary: Researchers developed a Python-based package (TensorZINB) using the TensorFlow deep learning framework to solve the zero-inflated negative binomial (ZINB) model for single cell RNA sequencing data analysis. They also proposed a hybrid model to further improve performance and systematically evaluated seven different statistical models. The study showed that TensorZINB outperformed existing ZINB solvers in terms of stability, computing speed, and performance.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Genetics & Heredity
Duah Alkam, Thidathip Wongsurawat, Intawat Nookaew, Anthony R. Richardson, David Ussery, Mark S. Smeltzer, Piroon Jenjaroenpun
Summary: TnSeq assays generate millions of nucleotide sequence reads to detect transposon insertion mutations in genes. PCR-based insertion enrichment does not significantly bias results, except for a subset of essential genes sensitive to PCR cycle number. nCATRAs, an amplification-free method, provides comparable results to traditional PCR-based methods.
MICROBIAL GENOMICS
(2021)
Review
Immunology
Francesca G. G. Tomasi, Eric J. J. Rubin
Summary: Despite significant advancements in the 20th century, tuberculosis (TB) remains a global health challenge, exacerbated by the COVID-19 pandemic. Improving TB chemotherapy through genetic and analytical tools can help identify and prioritize drug targets, leading to the rational design of treatment regimens that maximize bacterial killing and minimize treatment duration and relapse.
FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY
(2022)
Article
Environmental Sciences
Maria Bugallo, Maria Dolores Esteban, Manuel Francisco Marey-Perez, Domingo Morales
Summary: In recent decades, there have been changes in the occurrence of wildfires. It is necessary to develop accurate predictive models on a country scale to efficiently allocate firefighting resources. Mediterranean countries experience a high number of wildfires, mainly concentrated in the summer months. Zero-inflated negative binomial mixed models are suitable for analyzing this type of data and can provide useful prediction tools by considering both the occurrence and non-occurrence of fires. Additionally, a parametric bootstrap method is applied to estimate mean squared errors and construct prediction intervals.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Geosciences, Multidisciplinary
Frank Badu Osei, Alfred Stein, Veronica Andreo
Summary: Spatial disease modeling is an important tool in public health, and the use of zero-inflated mixture spatially varying coefficient models shows promising results for analyzing cholera data. The ZINB model outperformed the ZIP model in terms of fit and estimation of zero counts. The spatially varying effects of precipitation and temperature on cholera were found to have both increasing and decreasing gradients, emphasizing the importance of considering spatial factors in disease monitoring.
SPATIAL STATISTICS
(2022)
Article
Mathematics, Applied
Emrah Altun, Hana Alqifari, Mohamed S. Eliwa
Summary: Count regression models are important for modeling discrete dependent variables with known covariates. This study introduces a new model, the zero-inflated Poisson generalized Lindley regression model, to replace the zero-inflated negative-binomial regression model. The Poisson generalized-Lindley distribution is re-parametrized and its parameter estimation problem is discussed using maximum likelihood estimation. The efficiency of parameter estimation of the proposed model is evaluated through simulation studies and the success of the model in handling zero inflation is tested using two datasets. The proposed model outperforms the negative-binomial regression model in cases of over-dispersion and zero inflation.
Article
Biochemistry & Molecular Biology
Barbara Bosch, Michael A. De Jesus, Nicholas C. Poulton, Wenzhu Zhang, Curtis A. Engelhart, Anisha Zaveri, Sophie Lavalette, Nadine Ruecker, Carolina Trujillo, Joshua B. Wallach, Shuqi Li, Sabine Ehrt, Brian T. Chait, Dirk Schnappinger, Jeremy M. Rock
Summary: The study suggests that traditional genetic approaches may not accurately identify high-value bacterial targets, while using CRISPR technology to modulate gene expression can help differentiate bacteria's vulnerability to gene inhibition, identifying both highly vulnerable genes and invulnerable essential genes.
Article
Multidisciplinary Sciences
Esha Dutta, Michael A. DeJesus, Nadine Ruecker, Anisha Zaveri, Eun-Ik Koh, Christopher M. Sassetti, Dirk Schnappinger, Thomas R. Ioerger
Summary: Chemical-genetics (C-G) experiments are used to identify interactions between inhibitory compounds and bacterial genes, potentially revealing drug targets or other functionally interacting genes and pathways. By constructing a library of hypomorphic strains, treating them with inhibitory compounds, and using high-throughput sequencing, changes in relative abundance of individual mutants can be quantified. A new statistical method called CGA-LMM is proposed for analyzing C-G data, capturing the dependence of gene abundance in the hypomorph library on increasing drug concentrations through slope coefficients. This method was applied to analyze interactions between Mycobacterium tuberculosis hypomorph libraries and antibiotics, successfully identifying known target genes or expected interactions for the majority of drugs tested.
Article
Microbiology
Gregory H. Babunovic, Michael A. DeJesus, Barbara Bosch, Michael R. Chase, Thibault Barbier, Amy K. Dickey, Bryan D. Bryson, Jeremy M. Rock, Sarah M. Fortune
Summary: The study found that the application of all-trans-retinoic acid (ATRA) can enhance the control of Mycobacterium tuberculosis (Mtb) by human macrophages, which is achieved by altering macrophage cholesterol trafficking and lipid metabolism. In addition, CRISPR interference screening was used to identify specific genes required for Mtb survival in ATRA-activated macrophages.
Article
Biology
Clare M. Smith, Richard E. Baker, Megan K. Proulx, Bibhuti B. Mishra, Jarukit E. Long, Sae Woong Park, Ha-Na Lee, Michael C. Kiritsy, Michelle M. Bellerose, Andrew J. Olive, Kenan C. Murphy, Kadamba Papavinasasundaram, Frederick J. Boehm, Charlotte J. Reames, Rachel K. Meade, Brea K. Hampton, Colton L. Linnertz, Ginger D. Shaw, Pablo Hock, Timothy A. Bell, Sabine Ehrt, Dirk Schnappinger, Fernando Pardo-Manuel de Villena, Martin T. Ferris, Thomas R. Ioerger, Christopher M. Sassetti, Bavesh D. Kana
Summary: This study utilizes a genetically diverse Collaborative Cross mouse panel and a library of Mtb mutants to investigate the relationship between bacterial genetic requirements and host genetics and immunity. Global analysis reveals that many virulence pathways are only required in specific host microenvironments, and a large portion of the pathogen's genome has been maintained for fitness in a diverse population. The study identifies genetic variants across the mouse genome that are associated with both immunological and bacterial traits, providing a unique population for studying specific host-pathogen genetic interactions that influence pathogenesis.
Article
Microbiology
Shuqi Li, Nicholas C. Poulton, Jesseon S. Chang, Zachary A. Azadian, Michael A. DeJesus, Nadine Ruecker, Matthew D. Zimmerman, Kathryn A. Eckartt, Barbara Bosch, Curtis A. Engelhart, Daniel F. Sullivan, Martin Gengenbacher, Veronique A. Dartois, Dirk Schnappinger, Jeremy M. Rock
Summary: This study utilized a CRISPR interference chemical-genetics platform to uncover various drug resistant mechanisms in Mycobacterium tuberculosis (Mtb) and identified a potential new drug for treating tuberculosis.
NATURE MICROBIOLOGY
(2022)
Article
Microbiology
Nicholas C. Poulton, Zachary A. Azadian, Michael A. DeJesus, Jeremy M. Rock
Summary: Tuberculosis is a fatal bacterial infection, causing 1.5 million deaths globally each year. Drug-resistant strains of Mycobacterium tuberculosis (Mtb) have emerged, leading to efforts in developing novel drugs. The arabinogalactan biosynthetic enzyme DprE1 in Mtb is a promising drug target, with over a dozen inhibitory compounds identified. Among them, BTZ043 and PBTZ169 have shown promise and are in clinical trials. A study using CRISPRi chemical-genetic screen with PBTZ169 identified rv0678 as a negative regulator of the mmpS5/L5 drug efflux pump, which confers resistance to PBTZ169. Mutations in rv0678 are associated with resistance to another drug, bedaquiline. These results highlight the importance of monitoring for rv0678 mutations in ongoing clinical trials of BTZ043 and PBTZ169.
ANTIMICROBIAL AGENTS AND CHEMOTHERAPY
(2022)
Article
Biochemistry & Molecular Biology
Tomer M. Yaron, Brook E. Heaton, Tyler M. Levy, Jared L. Johnson, Tristan X. Jordan, Benjamin M. Cohen, Alexander Kerelsky, Ting-Yu Lin, Katarina M. Liberatore, Danielle K. Bulaon, Samantha J. Van Nest, Nikos Koundouros, Edward R. Kastenhuber, Marisa N. Mercadante, Kripa Shobana-Ganesh, Long He, Robert E. Schwartz, Shuibing Chen, Harel Weinstein, Olivier Elemento, Elena Piskounova, Benjamin E. Nilsson-Payant, Gina Lee, Joseph D. Trimarco, Kaitlyn N. Burke, Cait E. Hamele, Ryan R. Chaparian, Alfred T. Harding, Aleksandra Tata, Xinyu Zhu, Purushothama Rao Tata, Clare M. Smith, Anthony P. Possemato, Sasha L. Tkachev, Peter V. Hornbeck, Sean A. Beausoleil, Shankara K. Anand, Francois Aguet, Gad Getz, Andrew D. Davidson, Kate Heesom, Maia Kavanagh-Williamson, David A. Matthews, Benjamin R. tenOever, Lewis C. Cantley, John Blenis, Nicholas S. Heaton
Summary: This study reveals potential therapeutic targets for coronavirus-related diseases by investigating the phosphorylation mechanism of the viral N protein regulated by mammalian protein kinase families. Inhibitors of these protein kinases may have therapeutic potential against COVID-19 and other coronavirus-mediated diseases.
Article
Biochemistry & Molecular Biology
Joseph W. Saelens, Mollie I. Sweeney, Gopinath Viswanathan, Ana Maria Xet-Mull, Kristen L. Jurcic Smith, Dana M. Sisk, Daniel D. Hu, Rachel M. Cronin, Erika J. Hughes, W. Jared Brewer, Jorn Coers, Matthew M. Champion, Patricia A. Champion, Craig B. Lowe, Clare M. Smith, Sunhee Lee, Jason E. Stout, David M. Tobin
Summary: The human pathogen Mycobacterium tuberculosis can cause lung disease and disseminate to other tissues. This study identified an outbreak of M. tuberculosis with high rates of extrapulmonary dissemination and bone disease. The causal strain carried a full-length ancestral version of the effector protein EsxM, which exacerbated dissemination through enhancement of macrophage motility and egress from granulomas, as well as alterations in macrophage actin dynamics. Reconstitution of ancestral EsxM in a modern attenuated strain altered the migratory mode of infected macrophages and promoted bone disease in a zebrafish model. The presence of a derived nonsense variant in EsxM in major M. tuberculosis lineages suggests a role for EsxM in regulating dissemination.
Article
Immunology
Kaley M. Wilburn, Rachel K. Meade, Emma M. Heckenberg, Jacob Dockterman, Joern Coers, Christopher M. Sassetti, Andrew J. Olive, Clare M. Smith
Summary: This study investigates the role of immunity-related GTPase M (IRGM) proteins in Mycobacterium tuberculosis (Mtb) infection. The results show that Irgm1 gene plays a critical role in host protection against Mtb infection in mice, and Irgm2 and Irgm3 genes are functionally related to Irgm1. Additionally, the deletion of Irgm3 gene restores protective immunity in Irgm1-deficient mice infected with Mtb.
INFECTION AND IMMUNITY
(2023)
Article
Biochemistry & Molecular Biology
Andrew J. J. Olive, Clare M. M. Smith, Christina E. E. Baer, Joern Coers, Christopher M. M. Sassetti
Summary: Cell-intrinsic immune mechanisms play a role in controlling intracellular pathogens. Mycobacterium tuberculosis (Mtb) has evolved to resist cell-autonomous immunity and cause persistent infections. The cytokine IFN gamma induces cell-autonomous immunity, but Mtb can evade certain antimicrobial responses mediated by IFN gamma. The Guanylate binding proteins (GBPs), key host defense proteins, are able to control intracellular infections. While GBPs can restrict M. bovis BCG, their role in Mtb infection was unclear. This study reveals a novel function of the ESX1 virulence system in evading GBP-mediated immunity.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Immunology
Oyindamola O. Adefisayo, Erin R. Curtis, Clare M. Smith
Summary: The causative agent of tuberculosis, Mycobacterium tuberculosis, has evolved unique phenotypic traits through selective pressures within host cells, contributing to its evolutionary success. Understanding the genetic repertoire used by Mtb to drive virulence and host immune evasion is crucial but remains a challenge. In this review, the employment of mycobacterial genetic tools to study the host-pathogen interaction is evaluated, with a focus on the murine model.
INFECTION AND IMMUNITY
(2023)
Article
Multidisciplinary Sciences
Nuria Martinez, Lorissa J. Smulan, Michael L. Jameson, Clare M. Smith, Kelly Cavallo, Michelle Bellerose, John Williams, Kim West, Christopher M. Sassetti, Amit Singhal, Hardy Kornfeld
Summary: Diabetes mellitus, especially type 2 diabetes, increases the risk of developing tuberculosis. In a mouse model, it was found that mice with type 2 diabetes, induced by a high-fat diet and streptozotocin, had higher mortality, more severe lung pathology, and higher bacterial burden following Mycobacterium tuberculosis infection compared to mice treated with streptozotocin or high-fat diet alone. The elevated plasma glycerol level in the type 2 diabetes model mice was found to contribute to their susceptibility to infection, as glycerol is a preferred carbon source for M. tuberculosis.
NATURE COMMUNICATIONS
(2023)
Article
Genetics & Heredity
Rachel K. Meade, Jarukit E. Long, Adrian Jinich, Kyu Y. Rhee, David G. Ashbrook, Robert W. Williams, Christopher M. Sassetti, Clare M. Smith
Summary: The genetic differences among mammalian hosts and Mtb strains were studied to determine their role in tuberculosis patient outcomes. The study used a comprehensive library of Mtb transposon mutants to identify host and pathogen genetic factors involved in Mtb pathogenesis. A QTL hotspot on chromosome 6 associated with multiple Mtb genes was identified as a result of this study.
G3-GENES GENOMES GENETICS
(2023)
Article
Microbiology
Gregory H. Babunovic, Michael A. DeJesus, Barbara Bosch, Michael R. Chase, Thibault Barbier, Amy K. Dickey, Bryan D. Bryson, Jeremy M. Rock, Sarah M. Fortune
Summary: This study identifies that the treatment with ATRA can enhance the control ability of macrophages against Mycobacterium tuberculosis (Mtb) by affecting bacterial clearance through changes in macrophage cholesterol metabolism, and conducts the first Mtb CRISPR interference screen in the infection model, revealing certain Mtb genes specifically required to survive in ATRA-activated macrophages.
Article
Multidisciplinary Sciences
Esha Dutta, Michael A. DeJesus, Nadine Ruecker, Anisha Zaveri, Eun-Ik Koh, Christopher M. Sassetti, Dirk Schnappinger, Thomas R. Ioerger
Summary: Chemical-genetics experiments can identify interactions between inhibitory compounds and bacterial genes, revealing drug targets or functionally interacting genes. By using Linear Mixed Models, a statistical method known as CGA-LMM can analyze C-G data and detect candidate gene interactions based on their abundance changes with increasing drug concentrations.