{"entity": "researcher", "timestamp": "2026-08-08T16:31:09.445Z", "family": "Buetti-Dinh", "given": "Antoine", "initials": "A", "orcid": "0000-0002-6469-0296", "affiliations": ["Institute of Computational Science, Faculty of Informatics, Universit\u00e0 della Svizzera Italiana, Lugano, Switzerland", "Swiss Institute of Bioinformatics, Lausanne, Switzerland"], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/071a99356d6f4650a6707dc84777a66c.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/071a99356d6f4650a6707dc84777a66c"}}, "publications": [{"entity": "publication", "iuid": "a0852875f0e24bf78b3c291325fc9de9", "links": {"self": {"href": "https://publications.scilifelab.se/publication/a0852875f0e24bf78b3c291325fc9de9.json"}, "display": {"href": "https://publications.scilifelab.se/publication/a0852875f0e24bf78b3c291325fc9de9"}}, "title": "Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations.", "authors": [{"family": "Buetti-Dinh", "given": "Antoine", "initials": "A", "orcid": "0000-0002-6469-0296", "researcher": {"href": "https://publications.scilifelab.se/researcher/071a99356d6f4650a6707dc84777a66c.json"}}, {"family": "Herold", "given": "Malte", "initials": "M", "orcid": "0000-0003-2627-0159", "researcher": {"href": "https://publications.scilifelab.se/researcher/70759c28794141fbb123901947534ec4.json"}}, {"family": "Christel", "given": "Stephan", "initials": "S", "orcid": "0000-0003-0021-2452", "researcher": {"href": "https://publications.scilifelab.se/researcher/9db0f79d5ee144308ccb724e51959bc8.json"}}, {"family": "El Hajjami", "given": "Mohamed", "initials": "M"}, {"family": "Delogu", "given": "Francesco", "initials": "F"}, {"family": "Ilie", "given": "Olga", "initials": "O"}, {"family": "Bellenberg", "given": "S\u00f6ren", "initials": "S"}, {"family": "Wilmes", "given": "Paul", "initials": "P", "orcid": "0000-0002-6478-2924", "researcher": {"href": "https://publications.scilifelab.se/researcher/a0fa4b91d7384fda991fcda7c3df41be.json"}}, {"family": "Poetsch", "given": "Ansgar", "initials": "A"}, {"family": "Sand", "given": "Wolfgang", "initials": "W"}, {"family": "Vera", "given": "Mario", "initials": "M", "orcid": "0000-0002-1762-4421", "researcher": {"href": "https://publications.scilifelab.se/researcher/2a9ade6aac4e45399d1e1207a8b58398.json"}}, {"family": "Pivkin", "given": "Igor V", "initials": "IV"}, {"family": "Friedman", "given": "Ran", "initials": "R", "orcid": "0000-0001-8696-3104", "researcher": {"href": "https://publications.scilifelab.se/researcher/aff68ae331c349e189a6ecf511823fc3.json"}}, {"family": "Dopson", "given": "Mark", "initials": "M", "orcid": "0000-0002-9622-3318", "researcher": {"href": "https://publications.scilifelab.se/researcher/1dc9cc6dadf6483e88d855dc78709a59.json"}}], "type": "journal article", "published": "2020-01-21", "journal": {"title": "BMC Bioinformatics", "issn": "1471-2105", "volume": "21", "issue": "1", "pages": "23", "issn-l": "1471-2105"}, "abstract": "Network inference is an important aim of systems biology. It enables the transformation of OMICs datasets into biological knowledge. It consists of reverse engineering gene regulatory networks from OMICs data, such as RNAseq or mass spectrometry-based proteomics data, through computational methods. This approach allows to identify signalling pathways involved in specific biological functions. The ability to infer causality in gene regulatory networks, in addition to correlation, is crucial for several modelling approaches and allows targeted control in biotechnology applications.\n\nWe performed simulations according to the approximate Bayesian computation method, where the core model consisted of a steady-state simulation algorithm used to study gene regulatory networks in systems for which a limited level of details is available. The simulations outcome was compared to experimentally measured transcriptomics and proteomics data through approximate Bayesian computation.\n\nThe structure of small gene regulatory networks responsible for the regulation of biological functions involved in biomining were inferred from multi OMICs data of mixed bacterial cultures. Several causal inter- and intraspecies interactions were inferred between genes coding for proteins involved in the biomining process, such as heavy metal transport, DNA damage, replication and repair, and membrane biogenesis. The method also provided indications for the role of several uncharacterized proteins by the inferred connection in their network context.\n\nThe combination of fast algorithms with high-performance computing allowed the simulation of a multitude of gene regulatory networks and their comparison to experimentally measured OMICs data through approximate Bayesian computation, enabling the probabilistic inference of causality in gene regulatory networks of a multispecies bacterial system involved in biomining without need of single-cell or multiple perturbation experiments. This information can be used to influence biological functions and control specific processes in biotechnology applications.", "doi": "10.1186/s12859-019-3337-9", "pmid": "31964336", "labels": {"National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Stockholm (Genomics Production)": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "10.1186/s12859-019-3337-9"}, {"db": "pmc", "key": "PMC6975020"}], "notes": [], "created": "2020-07-08T13:03:37.375Z", "modified": "2024-01-16T13:48:43.057Z"}, {"entity": "publication", "iuid": "abfca60b81f644029343286d33478c2b", "links": {"self": {"href": "https://publications.scilifelab.se/publication/abfca60b81f644029343286d33478c2b.json"}, "display": {"href": "https://publications.scilifelab.se/publication/abfca60b81f644029343286d33478c2b"}}, "title": "Multi-omics Reveals the Lifestyle of the Acidophilic, Mineral-Oxidizing Model Species Leptospirillum ferriphilum T.", "authors": [{"family": "Christel", "given": "Stephan", "initials": "S", "orcid": "0000-0003-0021-2452", "researcher": {"href": "https://publications.scilifelab.se/researcher/9db0f79d5ee144308ccb724e51959bc8.json"}}, {"family": "Herold", "given": "Malte", "initials": "M", "orcid": "0000-0003-2627-0159", "researcher": {"href": "https://publications.scilifelab.se/researcher/70759c28794141fbb123901947534ec4.json"}}, {"family": "Bellenberg", "given": "S\u00f6ren", "initials": "S"}, {"family": "El Hajjami", "given": "Mohamed", "initials": "M"}, {"family": "Buetti-Dinh", "given": "Antoine", "initials": "A", "orcid": "0000-0002-6469-0296", "researcher": {"href": "https://publications.scilifelab.se/researcher/071a99356d6f4650a6707dc84777a66c.json"}}, {"family": "Pivkin", "given": "Igor V", "initials": "IV"}, {"family": "Sand", "given": "Wolfgang", "initials": "W"}, {"family": "Wilmes", "given": "Paul", "initials": "P"}, {"family": "Poetsch", "given": "Ansgar", "initials": "A"}, {"family": "Dopson", "given": "Mark", "initials": "M", "orcid": "0000-0002-9622-3318", "researcher": {"href": "https://publications.scilifelab.se/researcher/1dc9cc6dadf6483e88d855dc78709a59.json"}}], "type": "journal article", "published": "2018-02-01", "journal": {"volume": "84", "issn": "1098-5336", "issue": "3", "pages": "e02091-17", "title": "Appl. Environ. Microbiol.", "issn-l": "0099-2240"}, "abstract": "Leptospirillum ferriphilum plays a major role in acidic, metal-rich environments, where it represents one of the most prevalent iron oxidizers. These milieus include acid rock and mine drainage as well as biomining operations. Despite its perceived importance, no complete genome sequence of the type strain of this model species is available, limiting the possibilities to investigate the strategies and adaptations that Leptospirillum ferriphilum DSM 14647T (here referred to as Leptospirillum ferriphilumT) applies to survive and compete in its niche. This study presents a complete, circular genome of Leptospirillum ferriphilumT obtained by PacBio single-molecule real-time (SMRT) long-read sequencing for use as a high-quality reference. Analysis of the functionally annotated genome, mRNA transcripts, and protein concentrations revealed a previously undiscovered nitrogenase cluster for atmospheric nitrogen fixation and elucidated metabolic systems taking part in energy conservation, carbon fixation, pH homeostasis, heavy metal tolerance, the oxidative stress response, chemotaxis and motility, quorum sensing, and biofilm formation. Additionally, mRNA transcript counts and protein concentrations were compared between cells grown in continuous culture using ferrous iron as the substrate and those grown in bioleaching cultures containing chalcopyrite (CuFeS2). Adaptations of Leptospirillum ferriphilumT to growth on chalcopyrite included the possibly enhanced production of reducing power, reduced carbon dioxide fixation, as well as elevated levels of RNA transcripts and proteins involved in heavy metal resistance, with special emphasis on copper efflux systems. Finally, the expression and translation of genes responsible for chemotaxis and motility were enhanced.IMPORTANCELeptospirillum ferriphilum is one of the most important iron oxidizers in the context of acidic and metal-rich environments during moderately thermophilic biomining. A high-quality circular genome of Leptospirillum ferriphilumT coupled with functional omics data provides new insights into its metabolic properties, such as the novel identification of genes for atmospheric nitrogen fixation, and represents an essential step for further accurate proteomic and transcriptomic investigation of this acidophile model species in the future. Additionally, light is shed on adaptation strategies of Leptospirillum ferriphilumT for growth on the copper mineral chalcopyrite. These data can be applied to deepen our understanding and optimization of bioleaching and biooxidation, techniques that present sustainable and environmentally friendly alternatives to many traditional methods for metal extraction.", "doi": "10.1128/AEM.02091-17", "pmid": "29150517", "labels": {"National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Uppsala (Uppsala Genome Center)": "Service", "NGI Stockholm (Genomics Production)": "Service"}, "xrefs": [{"db": "pii", "key": "AEM.02091-17"}, {"db": "pmc", "key": "PMC5772234"}], "notes": [], "created": "2018-01-10T09:45:06.893Z", "modified": "2021-06-21T15:01:28.616Z"}]}