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196 results on '"Mhlanga, Musa M."'

1. Alternating high-fat diet enhances atherosclerosis by neutrophil reprogramming

Author

Lavillegrand, Jean-Rémi, Al-Rifai, Rida, Thietart, Sara, Guyon, Théo, Vandestienne, Marie, Cohen, Raphael, Duval, Vincent, Zhong, Xiaodan, Yen, Daniel, Ozturk, Mumin, Negishi, Yutaka, Konkel, Joanne, Pinteaux, Emmanuel, Lenoir, Olivia, Vilar, Jose, Laurans, Ludivine, Esposito, Bruno, Bredon, Marius, Sokol, Harry, Diedisheim, Marc, Saliba, Antoine-Emmanuel, Zernecke, Alma, Cochain, Clément, Haub, Jessica, Tedgui, Alain, Speck, Nancy A., Taleb, Soraya, Mhlanga, Musa M., Schlitzer, Andreas, Riksen, Niels P., and Ait-Oufella, Hafid

Published
2024
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2. A chromatin-regulated biphasic circuit coordinates IL-1β-mediated inflammation

Author

Fok, Ezio T., Moorlag, Simone J. C. F. M., Negishi, Yutaka, Groh, Laszlo A., dos Santos, Jéssica Cristina, Gräwe, Cathrin, Monge, Valerie Villacorta, Craenmehr, Daphne D. D., van Roosmalen, Mellanie, da Cunha Jolvino, David Pablo, Migliorini, Letícia Busato, Neto, Ary Serpa, Severino, Patricia, Vermeulen, Michiel, Joosten, Leo A. B., Netea, Mihai G., Fanucchi, Stephanie, and Mhlanga, Musa M.

Published
2024
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3. Trained immunity is regulated by T cell-induced CD40-TRAF6 signaling

Author

Jacobs, Maaike M.E., Maas, Rianne J.F., Jonkman, Inge, Negishi, Yutaka, Tielemans Zamora, Willem, Yanginlar, Cansu, van Heck, Julia, Matzaraki, Vasiliki, Martens, Joost H.A., Baltissen, Marijke, Vermeulen, Michiel, Morla-Folch, Judit, Ranzenigo, Anna, Wang, William, Umali, Martin, Ochando, Jordi, van der Vlag, Johan, Hilbrands, Luuk B., Joosten, Leo A.B., Netea, Mihai G., Mulder, Willem J.M., van Leent, Mandy M.T., Mhlanga, Musa M., Teunissen, Abraham J.P., Rother, Nils, and Duivenvoorden, Raphaël

Published
2024
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4. Trained immunity suppression determines kidney allograft survival

Author

Jonkman, Inge, Jacobs, Maaike M.E., Negishi, Yutaka, Yanginlar, Cansu, Martens, Joost H.A., Baltissen, Marijke, Vermeulen, Michiel, van den Hoogen, Martijn W.F., Baas, Marije, van der Vlag, Johan, Fayad, Zahi A., Teunissen, Abraham J.P., Madsen, Joren C., Ochando, Jordi, Joosten, Leo A.B., Netea, Mihai G., Mulder, Willem J.M., Mhlanga, Musa M., Hilbrands, Luuk B., Rother, Nils, and Duivenvoorden, Raphaël

Published
2024
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5. The Human Cell Atlas & Equity: Lessons Learned

Author

Majumder, Partha P., Mhlanga, Musa M., and Shalek, Alex K.

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

The Human Cell Atlas has been undergoing a massive effort to support global scientific equity. The co-leaders of its Equity Working Group share some lessons learned in the process.

Published
2020
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7. Interrogating RNA and protein spatial subcellular distribution in smFISH data with DypFISH

Author

Savulescu, Anca F., Brackin, Robyn, Bouilhol, Emmanuel, Dartigues, Benjamin, Warrell, Jonathan H., Pimentel, Mafalda R., Beaume, Nicolas, Fortunato, Isabela C., Dallongeville, Stephane, Boulle, Mikaël, Soueidan, Hayssam, Agou, Fabrice, Schmoranzer, Jan, Olivo-Marin, Jean-Christophe, Franco, Claudio A., Gomes, Edgar R., Nikolski, Macha, and Mhlanga, Musa M.

Published
2021
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8. Stability and Structural Properties of Gene Regulation Networks with Coregulation Rules

Author

Warrell, Jonathan H. and Mhlanga, Musa M.

Subjects
Statistics - Machine Learning, Quantitative Biology - Molecular Networks, Quantitative Biology - Quantitative Methods
Abstract

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated expression of modules (and module groups) of functionally related genes across the genome. Coregulation can also arise through the physical association of multi-gene complexes through chromosomal looping, which are then transcribed together. We present a general formalism for modeling coregulation rules in the framework of Random Boolean Networks (RBN), and develop specific models for transcription factor networks with modular structure (including module groups, and multi-input modules (MIM) with autoregulation) and multi-gene complexes (including hierarchical differentiation between multi-gene complex members). We develop a mean-field approach to analyse the stability of large networks incorporating coregulation, and show that autoregulated MIM and hierarchical gene-complex models can achieve greater stability than networks without coregulation whose rules have matching activation frequency. We provide further analysis of the stability of small networks of both kinds through simulations. We also characterize several general properties of the transients and attractors in the hierarchical coregulation model, and show using simulations that the steady-state distribution factorizes hierarchically as a Bayesian network in a Markov Jump Process analogue of the RBN model., Comment: 21 pages, 3 figures

Published
2016

9. Generalized Statistical Tests for mRNA and Protein Subcellular Spatial Patterning against Complete Spatial Randomness

Author

Warrell, Jonathan H., Savulescu, Anca F., Brackin, Robyn, and Mhlanga, Musa M.

Subjects
Statistics - Machine Learning, Quantitative Biology - Quantitative Methods, Statistics - Applications
Abstract

We derive generalized estimators for a number of spatial statistics that have been used in the analysis of spatially resolved omics data, such as Ripley's K, H and L functions, clustering index, and degree of clustering, which allow these statistics to be calculated on data modelled by arbitrary random measures (RMs). Our estimators generalize those typically used to calculate these statistics on point process data, allowing them to be calculated on RMs which assign continuous values to spatial regions, for instance to model protein intensity. The clustering index (H*) compares Ripley's H function calculated empirically to its distribution under complete spatial randomness (CSR), leading us to consider CSR null hypotheses for RMs which are not point-processes when generalizing this statistic. We thus consider restricted classes of completely random measures which can be simulated directly (Gamma processes and Marked Poisson Processes), as well as the general class of all CSR RMs, for which we derive an exact permutation-based H* estimator. We establish several properties of the estimators, including bounds on the accuracy of our general Ripley K estimator, its relationship to a previous estimator for the cross-correlation measure, and the relationship of our generalized H* estimator to previous statistics. To test the ability of our approach to identify spatial patterning, we use Fluorescent In Situ Hybridization (FISH) and Immunofluorescence (IF) data to probe for mRNA and protein subcellular localization patterns respectively in polarizing mouse fibroblasts on micropattened cells. We observe correlated patterns of clustering over time for corresponding mRNAs and proteins, suggesting a deterministic effect of mRNA localization on protein localization for several pairs tested, including one case in which spatial patterning at the mRNA level has not been previously demonstrated., Comment: 17 pages, 2 figures

Published
2016

10. A chromatin-regulated biphasic circuit coordinates IL-1β-mediated inflammation

Author

Fok, Ezio T., primary, Moorlag, Simone J. C. F. M., additional, Negishi, Yutaka, additional, Groh, Laszlo A., additional, dos Santos, Jéssica Cristina, additional, Gräwe, Cathrin, additional, Monge, Valerie Villacorta, additional, Craenmehr, Daphne D. D., additional, van Roosmalen, Mellanie, additional, da Cunha Jolvino, David Pablo, additional, Migliorini, Letícia Busato, additional, Neto, Ary Serpa, additional, Severino, Patricia, additional, Vermeulen, Michiel, additional, Joosten, Leo A. B., additional, Netea, Mihai G., additional, Fanucchi, Stephanie, additional, and Mhlanga, Musa M., additional

Published
2023
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12. Defining trained immunity and its role in health and disease

Author

Netea, Mihai G., Domínguez-Andrés, Jorge, Barreiro, Luis B., Chavakis, Triantafyllos, Divangahi, Maziar, Fuchs, Elaine, Joosten, Leo A. B., van der Meer, Jos W. M., Mhlanga, Musa M., Mulder, Willem J. M., Riksen, Niels P., Schlitzer, Andreas, Schultze, Joachim L., Stabell Benn, Christine, Sun, Joseph C., Xavier, Ramnik J., and Latz, Eicke

Published
2020
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15. Targeting innate immunity for tuberculosis vaccination

Author

Khader, Shabaana A., Divangahi, Maziar, Hanekom, Willem, Hill, Philip C., Maeurer, Markus, Makar, Karen W., Mayer-Barber, Katrin D., Mhlanga, Musa M., Nemes, Elisa, Schlesinger, Larry S., van Crevel, Reinout, Vankalayapati, Ramakrishna, Xavier, Ramnik J., Netea, Mihai G., and on behalf of the Bill and Melinda Gates Foundation Collaboration for TB Vaccine Discovery Innate Immunity Working Group

Subjects
Antigens -- Health aspects, Tuberculosis vaccines -- Health aspects, Epigenetic inheritance -- Health aspects, Lymphocytes -- Health aspects, BCG -- Health aspects, Antitubercular agents -- Health aspects, Medical research -- Health aspects, Vaccination -- Health aspects, Epidemiology -- Health aspects, Immune response -- Health aspects, Tuberculosis -- Development and progression -- Health aspects, Killer cells, T cells, B cells, Future predictions, Health care industry
Abstract

Vaccine development against tuberculosis (TB) is based on the induction of adaptive immune responses endowed with long-term memory against mycobacterial antigens. Memory B and T cells initiate a rapid and robust immune response upon encounter with Mycobacterium tuberculosis, thus achieving long-lasting protection against infection. Recent studies have shown, however, that innate immune cell populations such as myeloid cells and NK cells also undergo functional adaptation after infection or vaccination, a de facto innate immune memory that is also termed trained immunity. Experimental and epidemiological data have shown that induction of trained immunity contributes to the beneficial heterologous effects of vaccines such as bacille Calmette-Guerin (BCG), the licensed TB vaccine. Moreover, increasing evidence argues that trained immunity also contributes to the anti-TB effects of BCG vaccination. An interaction among immunological signals, metabolic rewiring, and epigenetic reprogramming underlies the molecular mechanisms mediating trained immunity in myeloid cells and their bone marrow progenitors. Future studies are warranted to explore the untapped potential of trained immunity to develop a future generation of TB vaccines that would combine innate and adaptive immune memory induction., Introduction Vaccination has made an enormous contribution to improving human and animal health over the last two centuries (1-6). Despite progress in developing vaccines against a large number of infections, [...]

Published
2019
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20. Long noncoding RNA CHROMR regulates antiviral immunity in humans

Author

van Solingen, Coen, primary, Cyr, Yannick, additional, Scacalossi, Kaitlyn R., additional, de Vries, Maren, additional, Barrett, Tessa J., additional, de Jong, Annika, additional, Gourvest, Morgane, additional, Zhang, Tracy, additional, Peled, Daniel, additional, Kher, Raadhika, additional, Cornwell, MacIntosh, additional, Gildea, Michael A., additional, Brown, Emily J., additional, Fanucchi, Stephanie, additional, Mhlanga, Musa M., additional, Berger, Jeffrey S., additional, Dittmann, Meike, additional, and Moore, Kathryn J., additional

Published
2022
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24. The Human Cell Atlas & Equity: Lessons Learned

Author

Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Massachusetts Institute of Technology. Department of Chemistry, Koch Institute for Integrative Cancer Research at MIT, Ragon Institute of MGH, MIT and Harvard, Broad Institute of MIT and Harvard, Majumder, Partha P, Mhlanga, Musa M, Shalek, Alexander K, Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Massachusetts Institute of Technology. Department of Chemistry, Koch Institute for Integrative Cancer Research at MIT, Ragon Institute of MGH, MIT and Harvard, Broad Institute of MIT and Harvard, Majumder, Partha P, Mhlanga, Musa M, and Shalek, Alexander K

Published
2022

29. Additional file 2 of Impact of rare and common genetic variation in the interleukin-1 pathway on human cytokine responses

Author

Van Deuren, Rosanne C., Arts, Peer, Cavalli, Giulio, Jaeger, Martin, Steehouwer, Marloes, Van De Vorst, Maartje, Gilissen, Christian, Joosten, Leo A. B., Dinarello, Charles A., Mhlanga, Musa M., Kumar, Vinod, Netea, Mihai G., Van De Veerdonk, Frank L., and Hoischen, Alexander

Abstract

Additional file 2: Supplementary Figures. Figure S1. Baseline characteristics of healthy individuals (n = 463) included in analysis. Figure S2. Average coverage depth per gene and overall for healthy individuals (n = 463) included in analysis. Figure S3. Correlation plots of significantly associated sets.

Published
2021
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30. Novel inner membrane retention signals in Pseudomonas aeruginosa lipoproteins

Author

Lewenza, Shawn, Mhlanga, Musa M., and Pugsley, Anthony P.

Subjects
Pseudomonas aeruginosa -- Physiological aspects, Pseudomonas aeruginosa -- Genetic aspects, Pseudomonas aeruginosa -- Research, Blood lipoproteins -- Physiological aspects, Blood lipoproteins -- Structure, Blood lipoproteins -- Research, Lipoproteins -- Physiological aspects, Lipoproteins -- Structure, Lipoproteins -- Research, Proteolipids -- Physiological aspects, Proteolipids -- Structure, Proteolipids -- Research, Biological sciences
Abstract

The ultimate membrane localization and function of most of the 185 predicted Pseudomonas aeruginosa PAO1 lipoproteins remain unknown. We constructed a fluorescent lipoprotein, [CSFp.sup.OmlA]-ChFP, by fusing the signal peptide and the first four amino acids of the P. aeruginosa outer membrane lipoprotein OmlA to the monomeric red fluorescent protein mCherry (ChFP). When cells were plasmolyzed with 0.5 M NaCl, the inner membrane separated from the outer membrane and formed plasmolysis bays. This permits the direct observation of fluorescence in either the outer or inner membrane. [CSFP.sup.OmlA]-ChFP was shown to localize in the outer membrane by fluorescence microscopy and immunoblotting analysis of inner and outer membrane fractions. The site-directed substitution of the amino acids at positions +2, +3, and +4 in [CSFP.sup.OmlA]-ChFP was performed to test the effects on lipoprotein localization of a series of amino acid sequences selected from a panel of predicted lipoproteins. We confirmed [Asp.sup.+2] and [Lys.sup.+3] [Ser.sup.+4] function as inner membrane retention signals and identified four novel inner membrane retention signals: [CK.sup.+2] [V.sup.+3] [E.sup.+4], [CG.sup.+2] [G.sup.+3] [G.sup.+4], [CG.sup.+2] [D.sup.+3] [D.sup.+4], and [CQ.sup.+2] [G.sup.+3] [S.sup.+4]. These inner membrane retention signals are found in 5% of the 185 predicted P. aeruginosa lipoproteins. Full-length chimeras of predicted lipoproteins PA4370 and PA3262 fused to mCherry were shown to reside in the inner membrane and showed a nonuniform or patchy distribution in the membrane. The optical sectioning of cells producing [PA4370.sup.CGDD-ChFP] and [PA3262.sup.CDSQ]-ChFP by confocal microscopy improved the resolution and indicated a helix-like localization pattern in the inner membrane. The method described here permits the in situ visualization of lipoprotein localization and should work equally well for other membrane-associated proteins.

Published
2008

32. BCG Vaccination Induces Long-Term Functional Reprogramming of Human Neutrophils

Author

Moorlag, Simone J.C.F.M., primary, Rodriguez-Rosales, Yessica Alina, additional, Gillard, Joshua, additional, Fanucchi, Stephanie, additional, Theunissen, Kate, additional, Novakovic, Boris, additional, de Bont, Cynthia M., additional, Negishi, Yutaka, additional, Fok, Ezio T., additional, Kalafati, Lydia, additional, Verginis, Panayotis, additional, Mourits, Vera P., additional, Koeken, Valerie A.C.M., additional, de Bree, L. Charlotte J., additional, Pruijn, Ger J.M., additional, Fenwick, Craig, additional, van Crevel, Reinout, additional, Joosten, Leo A.B., additional, Joosten, Irma, additional, Koenen, Hans, additional, Mhlanga, Musa M., additional, Diavatopoulos, Dimitri A., additional, Chavakis, Triantafyllos, additional, and Netea, Mihai G., additional

Published
2020
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33. Structural Variants Create New Topological-Associated Domains and Ectopic Retinal Enhancer-Gene Contact in Dominant Retinitis Pigmentosa

Author

de Bruijn, Suzanne E., primary, Fiorentino, Alessia, additional, Ottaviani, Daniele, additional, Fanucchi, Stephanie, additional, Melo, Uirá S., additional, Corral-Serrano, Julio C., additional, Mulders, Timo, additional, Georgiou, Michalis, additional, Rivolta, Carlo, additional, Pontikos, Nikolas, additional, Arno, Gavin, additional, Roberts, Lisa, additional, Greenberg, Jacquie, additional, Albert, Silvia, additional, Gilissen, Christian, additional, Aben, Marco, additional, Rebello, George, additional, Mead, Simon, additional, Raymond, F. Lucy, additional, Corominas, Jordi, additional, Smith, Claire E.L., additional, Kremer, Hannie, additional, Downes, Susan, additional, Black, Graeme C., additional, Webster, Andrew R., additional, Inglehearn, Chris F., additional, van den Born, L. Ingeborgh, additional, Koenekoop, Robert K., additional, Michaelides, Michel, additional, Ramesar, Raj S., additional, Hoyng, Carel B., additional, Mundlos, Stefan, additional, Mhlanga, Musa M., additional, Cremers, Frans P.M., additional, Cheetham, Michael E., additional, Roosing, Susanne, additional, and Hardcastle, Alison J., additional

Published
2020
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41. Impact of rare and common genetic variation in the Interleukin-1 pathway on human cytokine responses

Author

van Deuren, Rosanne C., primary, Arts, Peer, additional, Cavalli, Giulio, additional, Jaeger, Martin, additional, Steehouwer, Marloes, additional, van de Vorst, Maartje, additional, Gilissen, Christian, additional, Joosten, Leo A.B., additional, Dinarello, Charles A., additional, Mhlanga, Musa M., additional, Kumar, Vinod, additional, Netea, Mihai G., additional, van de Veerdonk, Frank L., additional, and Hoischen, Alexander, additional

Published
2020
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45. DypFISH: Dynamic Patterned FISH to Interrogate RNA and Protein Spatial and Temporal Subcellular Distribution

Author

Savulescu, Anca F., primary, Brackin, Robyn, additional, Bouilhol, Emmanuel, additional, Dartigues, Benjamin, additional, Warrell, Jonathan H., additional, Pimentel, Mafalda R., additional, Dallongeville, Stephane, additional, Schmoranzer, Jan, additional, Olivo-Marin, Jean-Christophe, additional, Gomes, Edgar R., additional, Nikolski, Macha, additional, and Mhlanga, Musa M., additional

Published
2019
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48. Immune genes are primed for robust transcription by proximal long noncoding RNAs located in nuclear compartments

Author

Fanucchi, Stephanie, primary, Fok, Ezio T., additional, Dalla, Emiliano, additional, Shibayama, Youtaro, additional, Börner, Kathleen, additional, Chang, Erin Y., additional, Stoychev, Stoyan, additional, Imakaev, Maxim, additional, Grimm, Dirk, additional, Wang, Kevin C., additional, Li, Guoliang, additional, Sung, Wing-Kin, additional, and Mhlanga, Musa M., additional

Published
2018
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