We are delighted to share the latest selections in the Molecular Omics Editor’s collection. This is a showcase of some of the best articles published in our journal, hand selected by our Associate Editors and Editorial Board members.

This selection is from our Associate Editor Richard Unwin. Richard graduated from the University of Nottingham with a BSc in Biology and MSc in Oncology before obtaining his PhD from the University of Leeds in 2001 in what was then the new field of Proteomics. He subsequently joined the University of Manchester, developing new methods for analysing cancer proteomes, including isobaric tagging, global and targeted analysis of protein phosphorylation, and methods for comparing proteomic and transcriptomic data.

In 2010 he moved to manage a new mass spectrometry research laboratory within the UK National Health Service, where he worked on the study of proteins and metabolites in chronic disease before returning to the University of Manchester in 2017 to continue a research programme developing tools for mass spectrometry data acquisition and analysis for the study of age-related chronic diseases.

Professor Unwin has highlighted some of their favourite recent articles below:

Integrative analysis of cancer dependency data and comprehensive phosphoproteomics data revealed the EPHA2-PARD3 axis as a cancer vulnerability in KRAS-mutant colorectal cancer
Daigo Gunji, Ryohei Narumi, Satoshi Muraoka, Junko Isoyama, Narumi Ikemoto, Mimiko Ishida, Takeshi Tomonaga, Yoshiharu Sakai, Kazutaka Obama and Jun Adachi
Mol. Omics, 2023, 19, 624-639

Richard’s comments
“Colorectal cancer (CRC) remains one of the most untreatable cancers. Here, the authors provide an in-depth analysis of the proteome and phosphoproteome of 35 CRC cell lines in order to correlate protein expression or signalling with mutation status in the KRAS and BRAF genes. Their study identified specific protein interactions and signalling pathways that are associated with specific genotypes, and further identified a series of tight junction-related proteins associated with hard-to-treat KRAS mutant cancers.”

Single cell proteomics analysis of drug response shows its potential as a drug discovery platform
Juerg Straubhaar, Alexandria D’Souza, Zachary Niziolek and Bodgan Budnik
Mol. Omics, 2024, 20, 6-18

Richard’s comments
“Single cell-based omics, in particular proteomics, are enhancing our fundamental understand of biology but provide unique challenges around speed and sensitivity. As such, methods are evolving rapidly as the field moves forward. This paper adds to this effort by modifying a well-established workflow to increase penetration into the single-cell proteome and provides good use cases for the technology in model systems.”

Proteome- and metabolome-level changes during early stages of clubroot infection in Brassica napus canola
Dinesh Adhikary, Devang Mehta, Anna Kisiala, Urmila Basu, R. Glen Uhrig, R. J. Neil Emery, Habibur Rahman and Nat N. V. Kav
Mol. Omics, 2024, 20, 265-282

Richard’s comments
“Canola is an important oilseed crop, yet worldwide yields are impacted significantly by infection with clubroot. In this paper, the authors perform an integrated proteomic and metabolomics analysis of infection-resistant and susceptible strains and provide the first look at the molecular changes in the root as a result of infection. Data integration and pathway analysis reveals a number of molecules which appear to be important in protection of infection, and these provide targets for future strains created either via gene editing or as markers for future strain development.”

Enjoyed these articles? Check out our latest publications and if you want the chance to be part of the next edition of our Editor’s collection, submit your research here.

We are delighted to share the latest selections in the Molecular Omics Editor’s collection. This is a showcase of some of the best articles published in our journal, hand selected by our Associate Editors and Editorial Board members.

This selection is from our Associate Editor Professor Hyungwon Choi. Hyungwon is an Associate Professor in the Department of Medicine at the National University of Singapore.

He and his team have actively developed computational and statistical solutions for the analysis of high-throughput molecular data and integration of heterogeneous multi-omics data. His main research topics include network-driven integration of multi-omics data, protein-centric analysis of genomic and transcriptomic data in large-scale clinical studies, and bioinformatics pipeline development for mass spectrometry data extraction in metabolomics and lipidomics.

Professor Choi has highlighted some of their favourite recent articles below:

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions
Muzaffer Arikan and Thilo Muth
Mol. Omics, 2023, 19, 607-623

Hyungwon’s comments
“Arikan and Muth provide a timely review of the current state in the use of high-throughput omics technologies in microbial community analysis. The authors describe the emerging landscape towards comprehensive, integrated multi-omic analysis and the bioinformatic tools enabling the objective. The article offers an insightful map of complex data processing workflows and recounts significant challenges in integrating heterogeneous, complex data to generate meaningful information.”

Generation of β-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids
Lisa Morisseau, Fumiya Tokito, Stéphane Poulain, Valerie Plaisance, Valerie Pawlowski, Soo Hyeon Kim, Cécile Legallais, Rachid Jellali, Yasuyuki Sakai, Amar Abderrahmani and Eric Leclerc
Mol. Omics, 2023, 19, 810-822

Hyungwon’s comments
“Morisseau et al. previously derived human pancreatic beta cells from hiPSCs in 3D spheroids that are functionally akin to beta cells. In this paper, they expanded on the previous work to characterize cell population diversity using single cell transcriptomics analysis. Their knowledge-driven interpretation of the data delineates the composition of beta-like cell subtypes including bi-hormonal cells and potential endocrine progenitors. The work nicely showcases the potential of the differentiation protocol in physiological conditions relevant to diabetes and the power of single cell gene expression analysis.”

Pancreatic cancer environment: from patient-derived models to single-cell omics
Ao Gu, Jiatong Li, Shimei Qiu, Shenglin Hao, Zhu-Ying Yue, Shuyang Zhai, Meng-Yao Li and Yingbin Liu
Mol. Omics, 2024, 20, 220-233

Hyungwon’s comments
“Gu et al. review the advantages and disadvantages of patient-derived models such as xenografts, organoids and explants over conventional cell cultures as experimental models for characterizing pancreatic cancer microenvironment. The authors highlight the importance of patient-derived models in preserving realistic tumor heterogeneity and complexity. In this context, they show how single cell (or spatially resolved) transcriptomics and epigenomics analysis, and potentially multi-omic approaches can decipher key biological signals in all three types of models.”

Enjoyed these articles? Check out our latest publications and if you want the chance to be part of the next edition of our Editor’s collection, submit your research here.