Ilnam Kang

@ilnamkang.bsky.social

https://orcid.org/0000-0003-2815-1735

Psychrophiles elude genomic prediction of optimal growth temperature | mSystems

Psychrophiles elude genomic prediction of optimal growth temperature | mSystems

Most prokaryotic taxa remain difficult to grow and study in culture, and their environmental preferences remain largely unquantified (1). As one example, we know that the optimal temperature for growth (OGT) can vary dramatically across prokaryotes, but the OGT values for most prokaryotic species found on Earth remain unknown. As OGT is an important determinant of when and where species will grow, being able to reliably infer OGT values is useful for many reasons, from identifying effective culturing strategies to predicting how the distributions of microbial taxa will shift in response to climate change (1). Because the phylogenetic coherence of this trait is weak, with even members of the same genus having variable OGTs (2), we cannot simply predict OGT values from taxonomic or phylogenetic information alone (3). Instead, given the vast quantity of genomic information now available for uncultured prokaryotes, there is broad interest in developing genome-based models to infer OGT for uncultured species. Pre-existing modeling efforts have leveraged various genomic features to infer OGT values with varying degrees of success. Examples of such models include those based on nucleotide sequences (4–10); amino acid sequences and protein annotations (8, 11–14); and a combination of features derived from DNA and protein data (15). Yet, because trait axes orthogonal to OGT also impact genome composition, composition alone is not sufficient to explain OGT differences between thermophiles and psychrophiles (16, 17).

journals.asm.org

It's out! Excited to present the Great Barrier Reef Microbial Genomes Database (GBR-MGD), a comprehensive DB of 1000s of high-quality prokaryote, virus, plasmid, and chromosome-level eukaryote MAGs using Nanopore long reads. Subthreads incoming. Please share widely. 🙂 www.nature.com/articles/s41...

The planktonic microbiome of the Great Barrier Reef - Nature

The Great Barrier Reef Microbial Genomes Database compiles prokaryotic, viral and eukaryotic genomes from seawater collected from the Great Barrier Reef, providing a rich resource for the study of mar...

nature.com

Genuine question for folx who look at bacterial phylogenies: How do you interpret the bootstrap support and posterior probabilities that you get on your tree estimates? Do you take them seriously? Do you think: "Wow, all 99%, that must be a reliable tree!"? 1/

We have a bunch of MAGs sitting in GenBank queues for many months. I run all MAGs through PGAP so they’re BLAST-able & assigned accessions, which I refer to when discussing genes in MAGs in papers. This has ground to a halt w/ NCBI processing delays in recent years. Is there anyway to expedite this?

Bacteriophage continue to have so much to teach us. It's in our interest to understand how they work and impact human & environmental health. New joint work led by @mariandm.bsky.social & @rantahan.bsky.social inferring single-cell latent period & burst size heterogeneity from population dynamics.

Inferring single-cell heterogeneity of bacteriophage lysis-associated life-history traits from population-scale dynamics

Theory-guided experiments reveal single-cell heterogeneity of lysis-associated bacteriophage traits from population scale data.

science.org

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Glad to see it finally out in #mSystems @asm.org! 🥳 See the thread below to read what it is about! journals.asm.org/doi/10.1128/...

Global distribution of isoprenoid quinones across Bacteria | mSystems

Isoprenoid quinones are small electron-carrying molecules found in the membranes of organisms that produce energy through photosynthesis or respiration and participate in other important cellular processes. Recent advances in the characterization of their biosynthesis pathways enable their automated annotation from genome analyses. In this article, we performed the genomic analysis of over 26,000 cultured and uncultured bacteria, which was complemented by literature data compiled on over 6,000 cultured bacteria. This enabled us to provide an unprecedented overview of quinone distribution across the bacterial diversity. Creating such a comprehensive data set revealed new information about quinone distribution and evolutionary paths and will facilitate future exploration of various aspects of quinone biology, including their role in the evolution and diversification of bacterial metabolism.

journals.asm.org

Sophie Abby@soabby.bsky.social · 11mo ago

Really glad to announce a new preprint from our lab: Global distribution of quinones in Bacteria! We here combine comparative genomics and text mining to leverage information on quinones distribution from thousands of articles describing new species and from dozens of thousands of genomes! 1/5

Hi ocean -omics folks, someone (a while back) mentioned to me that they thought the Tara Oceans metagenome sequencing effort did some "blanks" sequencing - negative controls intended to get at contam & artifacts. I can't find any mention of them in papers tho. Can anyone help me find 'em? thx!

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MBARI captured these views of glass squids in family Cranchiidae. I want to talk about some of the unique adaptations these Ghosts of the Midwater have & how they're adaptive to life in the twilight waters of the mesopelagic zone (200 m to 1000 m). (📷: Monterey Bay Aquarium Research Institute)