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At least 1,477 records · Page 82

Sequence-based generative AI design of versatile tryptophan synthases

Enzymes are powerful and sustainable catalysts, but their widespread application is limited by the difficulty of identifying functional starting points for optimization, creating a major bottleneck in early- stage biocatalyst discovery. Designing libraries of such starting enzymes remains particularly challenging. Here, we use the GenSLM protein language model to generate novel β-subunit of tryptophan synthase (TrpB) enzymes that express in Escherichia coli and are both stable and catalytically active. Many generated TrpBs also display significant substrate promiscuity, outperforming their natural counterparts on non-native substrates. Some even surpass laboratory-evolved TrpBs. Comparison of the most-active and most-promiscuous generated TrpB to its closest natural homolog confirms that the enhanced versatility is absent from the natural enzyme, highlighting the creative potential of generative models. These results demonstrate that the generated TrpBs not only preserve natural structure and function but also acquire non-natural properties, establishing generative models as powerful tools for biocatalyst discovery and engineering.

biocatalysis↗

BiG-SCAPE 2.0 and BiG-SLiCE 2.0: scalable, accurate and interactive sequence clustering of metabolic gene clusters

Microbial metabolic gene clusters encode the biosynthesis or catabolism of metabolites that facilitate ecological specialization, mediate microbiome interactions and constitute a major source of medicines and crop protection agents. Here, we present BiG-SCAPE and BiG-SLiCE 2.0, next-generation methods that facilitate scalable, accurate and interactive gene cluster analyses. BiG-SCAPE 2.0 updates its classification, alignment methods, and visualizations, enabling more accurate analysis, up to 8x faster runtimes and halved memory requirements. BiG-SLiCE 2.0 updates its distance metric, pHMM database, and classification logic, resulting in increased sensitivity nearing that of BiG-SCAPE. Analysis of 260,630 biosynthetic gene clusters from publicly available genomes reveals that both tools generate concurring estimates of gene cluster diversity, thus providing significantly extended methodological support for recent evidence indicating that the vast majority of natural product diversity remains unexplored. Together, these updates will facilitate global genome mining efforts for natural product discovery and microbiome analyses scalable with current data sizes.

Draisma, Arjan [Wageningen University & Research (↗

An evaporite sequence from ancient brine recorded in Bennu samples

Evaporation or freezing of water-rich fluids with dilute concentrations of dissolved salts can produce brines, as observed in closed basins on Earth and detected by remote sensing on icy bodies in the outer Solar System. The mineralogical evolution of these brines is well understood in regard to terrestrial environments, but poorly constrained for extraterrestrial systems owing to a lack of direct sampling. Here we report the occurrence of salt minerals in samples of the asteroid (101955) Bennu returned by the OSIRIS-REx mission. These include sodium-bearing phosphates and sodium-rich carbonates, sulfates, chlorides and fluorides formed during evaporation of a late-stage brine that existed early in the history of Bennu’s parent body. Discovery of diverse salts would not be possible without mission sample return and careful curation and storage, because these decompose with prolonged exposure to Earth’s atmosphere. Similar brines probably still occur in the interior of icy bodies Ceres and Enceladus, as indicated by spectra or measurement of sodium carbonate on the surface or in plumes.

58 GEOSCIENCES↗

Cross-platform analysis of public responses to the 2019 Ridgecrest earthquake sequence on Twitter and Reddit

Online social networks (OSNs) have become a powerful tool to study collective human responses to extreme events such as earthquakes. Most previous research concentrated on a single platform and utilized users’ behaviors on a single platform to study people’s general responses. In this study, we explore the characteristics of people’s behaviors on different OSNs and conduct a cross-platform analysis of public responses to earthquakes. Our findings support the Uses and Gratification theory that users on Reddit and Twitter are engaging with platforms that they may feel best reflect their sense of self. Using the 2019 Ridgecrest earthquakes as our study cases, we collected 510,579 tweets and 45,770 Reddit posts (including 1437 submissions and 44,333 comments) to answer the following research questions: (1) What were the similarities and differences between public responses on Twitter and Reddit? (2) Considering the different mechanisms of Twitter and Reddit, what unique information of public responses can we learn from Reddit as compared with Twitter? By answering these research questions, we aim to bridge the gap of cross-platform public responses research towards natural hazards. Our study evinces that the users on the two different platforms have both different topics of interest and different sentiments towards the same earthquake, which indicates the necessity of investigating cross-platform OSNs to reveal a more comprehensive picture of people’s general public responses towards certain disasters. Our analysis also finds that r/conspiracy subreddit is one of the major venues where people discuss the 2019 Ridgecrest earthquakes on Reddit and different misinformation/conspiracies spread on Twitter and Reddit platforms (e.g., “Big one is coming” on Twitter and “Nuclear test” on Reddit).

58 GEOSCIENCES↗

Sequence similarity between SARS-CoV-2 nucleocapsid and multiple sclerosis-associated proteins provides insight into viral neuropathogenesis following infection

Abstract The novel coronavirus SARS-CoV-2 continues to cause death and disease throughout the world, underscoring the necessity of understanding the virus and host immune response. From the start of the pandemic, a prominent pattern of central nervous system (CNS) pathologies, including demyelination, has emerged, suggesting an underlying mechanism of viral mimicry to CNS proteins. We hypothesized that immunodominant epitopes of SARS-CoV-2 share homology with proteins associated with multiple sclerosis (MS). Using PEPMatch, a newly developed bioinformatics package which predicts peptide similarity within specific amino acid mismatching parameters consistent with published MHC binding capacity, we discovered that nucleocapsid protein shares significant overlap with 22 MS-associated proteins, including myelin proteolipid protein (PLP). Further computational evaluation demonstrated that this overlap may have critical implications for T cell responses in MS patients and is likely unique to SARS-CoV-2 among the major human coronaviruses. Our findings substantiate the hypothesis of viral molecular mimicry in the pathogenesis of MS and warrant further experimental exploration.

60 APPLIED LIFE SCIENCES↗