bims-micpro 2024-06-02 papers

Issue of 2024‒06‒02
five papers selected by
Thomas Farid Martínez, University of California, Irvine

Front Mol Neurosci. 2024 ;17 1386219

Small but mighty: the rise of microprotein biology in neuroscience.

Erin E Duffy, Elena G Assad, Brian T Kalish, Michael E Greenberg.

The mammalian central nervous system coordinates a network of signaling pathways and cellular interactions, which enable a myriad of complex cognitive and physiological functions. While traditional efforts to understand the molecular basis of brain function have focused on well-characterized proteins, recent advances in high-throughput translatome profiling have revealed a staggering number of proteins translated from non-canonical open reading frames (ncORFs) such as 5' and 3' untranslated regions of annotated proteins, out-of-frame internal ORFs, and previously annotated non-coding RNAs. Of note, microproteins < 100 amino acids (AA) that are translated from such ncORFs have often been neglected due to computational and biochemical challenges. Thousands of putative microproteins have been identified in cell lines and tissues including the brain, with some serving critical biological functions. In this perspective, we highlight the recent discovery of microproteins in the brain and describe several hypotheses that have emerged concerning microprotein function in the developing and mature nervous system.

Keywords: DNA repair; RNA translation; brain; mammalian; microprotein; mitochondrial

DOI: https://doi.org/10.3389/fnmol.2024.1386219

Sci Rep. 2024 05 27. 14(1): 12090

Micropeptide AF127577.4-ORF hidden in a lncRNA diminishes glioblastoma cell proliferation via the modulation of ERK2/METTL3 interaction.

Baoshun Du, Zheying Zhang, Linlin Jia, Huan Zhang, Shuai Zhang, Haijun Wang, Zhenguo Cheng.

Micropeptides hidden in long non-coding RNAs (lncRNAs) have been uncovered to program various cell-biological changes associated with malignant transformation-glioblastoma (GBM) cascade. Here, we identified and characterized a novel hidden micropeptide implicated in GBM. We screened potential candidate lncRNAs by establishing a workflow involving ribosome-bound lncRNAs, publicly available MS/MS data, and prognosis-related lncRNAs. Micropeptide expression was detected by western blot (WB), immunofluorescence (IF), and immunohistochemistry (IHC). Cell proliferation rate was assessed by calcein/PI staining and EdU assay. Proteins interacted with the micropeptide were analyzed by proteomics after co-immunoprecipitation (Co-IP). We discovered that lncRNA AF127577.4 indeed encoded an endogenous micropeptide, named AF127577.4-ORF. AF127577.4-ORF was associated with GBM clinical grade. In vitro, AF127577.4-ORF could suppress GBM cell proliferation. Moreover, AF127577.4-ORF reduced m6A methylation level of GBM cells. Mechanistically, AF127577.4-ORF diminished ERK2 interaction with m6A reader methyltransferase like 3 (METTL3) and downregulated phosphorylated ERK (p-ERK) level. The ERK inhibitor reduced p-ERK level and downregulated METTL3 protein expression. AF127577.4-ORF weakened the stability of METTL3 protein by ERK. Also, AF127577.4-ORF suppressed GBM cell proliferation via METTL3. Our study identifies a novel micropeptide AF127577.4-ORF hidden in a lncRNA, with a potent anti-proliferating function in GBM by diminishing METTL3 protein stability by reducing the ERK2/METTL3 interaction. This micropeptide may be beneficial for development of therapeutic strategies against GBM.

Keywords: ERK2; Glioblastoma; METTL3; Micropeptide; lncRNA AF127577.4

DOI: https://doi.org/10.1038/s41598-024-62710-y

Plant Physiol. 2024 May 29. pii: kiae311. [Epub ahead of print]

NCPbook: a comprehensive database of non-canonical peptides.

Abdul Sami, Mengjia Fu, Haoqiang Yin, Usman Ali, Lei Tian, Shunxi Wang, Jinghua Zhang, Xueyan Chen, Hehuan Li, Minghui Chen, Wen Yao, Liuji Wu.

Non-canonical peptides (NCPs) are a class of peptides generated from regions previously thought of as non-coding, such as introns, 5' untranslated regions (UTRs), 3' UTRs, and intergenic regions. In recent years, the significance and diverse functions of NCPs have come to light, yet a systematic and comprehensive NCP database remains absent. Here, we developed NCPbook (https://ncp.wiki/ncpbook/), a database of evidence-supported NCPs, which aims to provide a resource for efficient exploration, analysis, and manipulation of NCPs. NCPbook incorporates data from diverse public databases and scientific literature. The current version of NCPbook includes 180,676 NCPs across 29 different species, evidenced by mass spectrometry (MS), ribosome profiling (Ribo-seq), or molecular experiments (ME). These NCPs are distributed across kingdoms, comprising 123,408 from 14 plant species, 56,999 from seven animal species, and 269 from eight microbial species. Furthermore, NCPbook encompasses 9,166 functionally characterized NCPs playing important roles in immunity, stress resistance, growth, and development. Equipped with a user-friendly interface, NCPbook allows users to search, browse, visualize, and retrieve data, making it an indispensable platform for researching NCPs in various plant, animal, and microbial species.

Keywords: Ribo-seq; database; mass spectrometry; non-canonical peptides; non-coding regions

DOI: https://doi.org/10.1093/plphys/kiae311

Comput Biol Med. 2024 May 27. pii: S0010-4825(24)00745-5. [Epub ahead of print]177 108660

MicroProteinDB: A database to provide knowledge on sequences, structures and function of ncRNA-derived microproteins.

Yinan Liang, Dezhong Lv, Kefan Liu, Liting Yang, Huan Shu, Luan Wen, Chongwen Lv, Qisen Sun, Jiaqi Yin, Hui Liu, Juan Xu, Zhigang Liu, Na Ding.

Omics-based technologies have revolutionized our comprehension of microproteins encoded by ncRNAs, revealing their abundant presence and pivotal roles within complex functional landscapes. Here, we developed MicroProteinDB (http://bio-bigdata.hrbmu.edu.cn/MicroProteinDB), which offers and visualizes the extensive knowledge to aid retrieval and analysis of computationally predicted and experimentally validated microproteins originating from various ncRNA types. Employing prediction algorithms grounded in diverse deep learning approaches, MicroProteinDB comprehensively documents the fundamental physicochemical properties, secondary and tertiary structures, interactions with functional proteins, family domains, and inter-species conservation of microproteins. With five major analytical modules, it will serve as a valuable knowledge for investigating ncRNA-derived microproteins.

Keywords: Conformation; Conservation; Interaction; Knowledge; Microprotein; ncRNA

DOI: https://doi.org/10.1016/j.compbiomed.2024.108660

Front Microbiol. 2024 ;15 1335310

Integrated sequence and -omic features reveal novel small proteome of Mycobacterium tuberculosis.

Priyansha Raj Sinha, Rami Balasubramanian, Shubhada R Hegde.

Bioinformatic studies on small proteins are under-represented due to difficulties in annotation posed by their small size. However, recent discoveries emphasize the functional significance of small proteins in cellular processes including cell signaling, metabolism, and adaptation to stress. In this study, we utilized a Random Forest classifier trained on sequence features, RNA-Seq, and Ribo-Seq data to uncover small proteins (smORFs) in M. tuberculosis. Independent predictions for the exponential and starvation conditions resulted in 695 potential smORFs. We examined the functional implications of these smORFs using homology searches, LC-MS/MS, and ChIP-seq data, testing their expression in diverse growth conditions, and identifying protein domains. We provide evidence that some of these smORFs could be part of operons, or exist as upstream ORFs. This expanded data resource for the proteins of M. tuberculosis would aid in fine-tuning the existing protein and gene regulatory networks, thereby improving system-wide studies. The primary goal of this study was to uncover and characterize smORFs in M. tuberculosis through bioinformatic analysis, shedding light on their functional roles and genomic organization. Further investigation of these potential smORFs would provide valuable insights into the genome organization and functional diversity of the M. tuberculosis proteome.

Keywords: RNA-Seq; Random Forest; Ribo-Seq; coupled ORFs; small proteins

DOI: https://doi.org/10.3389/fmicb.2024.1335310