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- Buetti-Dinh, Antoine, 1984-, et al.
(author)
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Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations
- 2020
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In: BMC Bioinformatics. - : BioMed Central (BMC). - 1471-2105. ; 21:1, s. 1-15
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Journal article (peer-reviewed)abstract
- Background: 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. Methods: We 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. Results: The 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. Conclusions: The 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.
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- Buetti-Dinh, Antoine, 1984-, et al.
(author)
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Systems biology of acidophile biofilms for efficient metal extraction
- 2020
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 7:1, s. 1-10
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Journal article (peer-reviewed)abstract
- Society's demand for metals is ever increasing while stocks of high-grade minerals are being depleted. Biomining, for example of chalcopyrite for copper recovery, is a more sustainable biotechnological process that exploits the capacity of acidophilic microbes to catalyze solid metal sulfide dissolution to soluble metal sulfates. A key early stage in biomining is cell attachment and biofilm formation on the mineral surface that results in elevated mineral oxidation rates. Industrial biomining of chalcopyrite is typically carried out in large scale heaps that suffer from the downsides of slow and poor metal recoveries. In an effort to mitigate these drawbacks, this study investigated planktonic and biofilm cells of acidophilic (optimal growth pH < 3) biomining bacteria. RNA and proteins were extracted, and high throughput "omics" performed from a total of 80 biomining experiments. In addition, micrographs of biofilm formation on the chalcopyrite mineral surface over time were generated from eight separate experiments. The dataset generated in this project will be of great use to microbiologists, biotechnologists, and industrial researchers.
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- Rafati, Nima, et al.
(author)
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Reconstruction of the birth of a male sex chromosome present in Atlantic herring
- 2020
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In: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy Of Sciences. - 0027-8424 .- 1091-6490. ; 117:39, s. 24359-24368
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Journal article (peer-reviewed)abstract
- The mechanisms underlying sex determination are astonishingly plastic. Particularly the triggers for the molecular machinery, which recalls either the male or female developmental program, are highly variable and have evolved independently and repeatedly. Fish show a huge variety of sex determination systems, including both genetic and environmental triggers. The advent of sex chromosomes is assumed to stabilize genetic sex determination. However, because sex chromosomes are notoriously cluttered with repetitive DNA and pseudogenes, the study of their evolution is hampered. Here we reconstruct the birth of a Y chromosome present in the Atlantic herring. The region is tiny (230 kb) and contains only three intact genes. The candidate male-determining gene BMPR1BBY encodes a truncated form of a BMP1B receptor, which originated by gene duplication and translocation and underwent rapid protein evolution. BMPR1BBY phosphorylates SMADs in the absence of ligand and thus has the potential to induce testis formation. The Y region also contains two genes encoding subunits of the sperm-specific Ca2+ channel CatSper required for male fertility. The herring Y chromosome conforms with a characteristic feature of many sex chromosomes, namely, suppressed recombination between a sex-determining factor and genes that are beneficial for the given sex. However, the herring Y differs from other sex chromosomes in that suppression of recombination is restricted to an ∼500-kb region harboring the male-specific and sex-associated regions. As a consequence, any degeneration on the herring Y chromosome is restricted to those genes located in the small region affected by suppressed recombination.
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