Abstract:
:Small open reading frames (smORFs) and their encoded microproteins play central roles in microbes. However, there is a vast unexplored space of smORFs within human-associated microbes. A recent bioinformatic analysis used evolutionary conservation signals to enhance prediction of small protein families. To facilitate the annotation of specific smORFs, we introduce SmORFinder. This tool combines profile hidden Markov models of each smORF family and deep learning models that better generalize to smORF families not seen in the training set, resulting in predictions enriched for Ribo-seq translation signals. Feature importance analysis reveals that the deep learning models learn to identify Shine-Dalgarno sequences, deprioritize the wobble position in each codon, and group codon synonyms found in the codon table. A core-genome analysis of 26 bacterial species identifies several core smORFs of unknown function. We pre-compute smORF annotations for thousands of RefSeq isolate genomes and Human Microbiome Project metagenomes and provide these data through a public web portal.
journal_name
Cell Host Microbejournal_title
Cell host & microbeauthors
Durrant MG,Bhatt ASdoi
10.1016/j.chom.2020.11.002subject
Has Abstractpub_date
2021-01-13 00:00:00pages
121-131.e4issue
1eissn
1931-3128issn
1934-6069pii
S1931-3128(20)30619-3journal_volume
29pub_type
杂志文章abstract::The clinically silent Plasmodium liver stage is an obligatory step in the establishment of malaria infection and disease. We report here that expression of heme oxygenase-1 (HO-1, encoded by Hmox1) is upregulated in the liver following infection by Plasmodium berghei and Plasmodium yoelii sporozoites. HO-1 overexpress...
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