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DIA workflow optimization with 3 species for low input

ABSTRACT: we systematically evaluated multiple factors in low-input DIA workflows on an Astral MS, including MS acquisition parameters, data analysis software (DIA-NN, Spectronaut, and FragPipe), LC separation gradient lengths, database searching algorithms, and protein quantification approaches. Using three-species proteome samples (human, yeast, and E. coli) with total input ranging from 0.1 ng to 10 ng and predefined quantity ratios, we focused on proteome coverage, quantification accuracy, and precision, which are the most important considerations when applying these methods in biological applications. Our evaluation suggested a preferred DIA workflow for low-input samples, which involves using a FAIMS interface, DIA-NN-based library-free database search with the enabled match between runs (MBR) function, and MS1-level protein quantification with the maxLFQ algorithm.

INSTRUMENT(S): Orbitrap Astral

ORGANISM(S): Escherichia Coli (ncbitaxon:562) Homo Sapiens (ncbitaxon:9606) Saccharomyces Cerevisiae (ncbitaxon:4932)

SUBMITTER: Ying Zhu

PROVIDER: MSV000098763 | MassIVE | Thu Aug 07 16:54:00 BST 2025

SECONDARY ACCESSION(S): PXD067103

REPOSITORIES: MassIVE

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Project description:Purpose: The goals of this study is to determine the best method of gene expression quantification (RNA-seq, Microarray, NanoString) and amplification kits adapted to low-input and/or low-quality RNA samples (FFPE samples) Methods: Mouse bladder cancer cell line (mouse bladder cancer cell line, BC57) and mouse normal mouse normal urothelium were fixed in formalin and embedded in paraffin (FFPE), andfesh frozen (FF) in liquid nitrogen. The total RNA of these 4 samples were tested by 3 technologies (NanoString, RNA-seq and Microarray) and the results were compared to its reference (high-quality and high-input RNA of mouse bladder cancer cell line and mouse normal mouse normal urothelium). For NanoString with low-input RNA samples, each sample was tested by NanoString quantification after amplification by SMARTer Stranded Total RNA-Seq Kit - Pico Input mammelian and Ovation SoLo NuGEN RNA-seq System, and NanoString based on PCR approach with three input quantities: 50pg, 250pg and 2ng of total RNA, except for NanoString quantification after amplification by SMARTer Stranded Total RNA-Seq Kit - Pico Input mammelian kit for which the minimum recommended quantity was 250pg of total RNA. NanoString direct quantification was also done for FF and FFPE samples at high amount (50ng of total RNA) and results obtained from FF samples were considered as the reference. To determine which is the method for NanoString technology, low-input and low-quality RNA samples, we performed NanoString control quality metrics, principal component analysis, and a differential analysis between the mouse bladder cancer cell lines and the mouse normal mouse normal urothelium for each input quantity, amplification method and method of sample preservation (FF or FFPE). Results: The NanoString based PCR based approach is recommended for quantification of gene expression of FFPE and FF samples from 250pg of total RNA. However, NanoString quantification after amplification by SMARTer Stranded Total RNA-Seq Kit - Pico Input mammelian and Ovation SoLo NuGEN RNA-seq System is not recommended for FF and FFPE from low-input samples.

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DIA workflow optimization with 3 species for low input

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