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Stability of proteins at high temperature has been a topic of interest for many years, as this attribute is favourable for applications ranging from therapeutics to industrial chemical manufacturing. Our current understanding and methods for designing high-temperature stability into target proteins are inadequate. To drive innovation in this space, we have curated a large dataset, learn2thermDB, of protein-temperature examples, totalling 24 million instances, and paired proteins across temperatures based on homology, yielding 69 million protein pairs - orders of magnitude larger than the current largest. This important step of pairing allows for study of high-temperature stability in a sequence-dependent manner in the big data era. The data pipeline is parameterized and open, allowing it to be tuned by downstream users. We further show that the data contains signal for deep learning. This data offers a new doorway towards thermal stability design models. [ABSTRACT FROM AUTHOR]

Mass-Suite (MSS) is a Python-based, open-source software package designed to analyze high-resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) data, particularly for water quality assessment and other environmental applications. MSS provides flexible, user-defined workflows for HRMS data processing and analysis, including both basic functions (e.g., feature extraction, data reduction, feature annotation, data visualization, and statistical analyses) and advanced exploratory data mining and predictive modeling capabilities that are not provided by currently available open-source software (e.g., unsupervised clustering analyses, a machine learning-based source tracking and apportionment tool). As a key advance, most core MSS functions are supported by machine learning algorithms (e.g., clustering algorithms and predictive modeling algorithms) to facilitate function accuracy and/or efficiency. MSS reliability was validated with mixed chemical standards of known composition, with 99.5% feature extraction accuracy and ~ 52% overlap of extracted features relative to other open-source software tools. Example user cases of laboratory data evaluation are provided to illustrate MSS functionalities and demonstrate reliability. MSS expands available HRMS data analysis workflows for water quality evaluation and environmental forensics, and is readily integrated with existing capabilities. As an open-source package, we anticipate further development of improved data analysis capabilities in collaboration with interested users. [ABSTRACT FROM AUTHOR]

Methylotrophs, organisms able to gain energy and carbon from compounds containing no carbon–carbon bonds, such as methane, methanol and methylated amines, are widespread in nature. However, knowledge of their nutrient preference and their metabolism is mostly based on experiments with cultures grown in defined laboratory conditions. Here, we use transcriptomics to explore the activity of one methylotroph, Methyotenera mobilis in its natural environment, lake sediment from which it has been previously isolated. Cells encapsulated in incubation cassettes were exposed to sediment conditions, with or without supplementation with a carbon/energy source (methylamine), and gene-expression patterns were compared for those cells to patterns for cells incubated in a defined medium supplemented with methylamine. A few specific trends in gene expression were observed at in situ conditions that may be of environmental significance, as follows. Expression of genes for the linear formaldehyde oxidation pathway linked to tetrahydromethanopterin increased, suggesting an important role for this pathway in situ, in contrast to laboratory condition culture, in which the cyclic ribulose monophosphate pathway seemed to be the major route for formaldehyde oxidation. Along with the ribulose monophosphate cycle that is also a major pathway for assimilating C1 units, the methylcitric acid cycle seemd to be important in situ, suggesting that multicarbon compounds may be the natural carbon and/or energy substrates for M. mobilis, challenging the notion of an obligately methylotrophic lifestyle for this bacterium. We also detected a major switch in expression of genes responsible for the mode of motility between different conditions: from flagellum-enabled motility in defined medium to in situ expression of pili known to be involved in twitching motility and adherence. Overall, this study offers a novel approach for gaining insights into the lifestyle of individual microbes in their native environments. [ABSTRACT FROM AUTHOR]