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Total RNA was extracted from infected and mock-infected HeLa cells, and relative mRNA levels were quantified by RT-qPCR using PUM1 as the reference gene. Expression levels in mock-infected samples were set to 1, and infected sample values are shown as fold change relative to mock. Data represent mean ± s.e.m. from three biological replicates. Statistical significance was determined using multiple t-tests, *p < 0.05.

Journal: bioRxiv

Article Title: Deep Learning-Driven Discovery of Mitochondrial Factors Modulating Influenza A Virus Infection

doi: 10.64898/2026.02.25.707858

Figure Lengend Snippet: Total RNA was extracted from infected and mock-infected HeLa cells, and relative mRNA levels were quantified by RT-qPCR using PUM1 as the reference gene. Expression levels in mock-infected samples were set to 1, and infected sample values are shown as fold change relative to mock. Data represent mean ± s.e.m. from three biological replicates. Statistical significance was determined using multiple t-tests, *p < 0.05.

Article Snippet: The values were transformed to a linear scale and plotted on graphs. qPCR oligonucleotides for the knockdown of targeted genes were purchased from Bioneer.

Techniques: Infection, Quantitative RT-PCR, Gene Expression

a, IFN-βmRNA relative expression. HeLa cells were transfected with siRNAs targeting individual mitochondrial genes or a non-targeting control (siControl), followed by infection with influenza A virus. IFN-β mRNA levels were measured by quantitative PCR (qPCR), using PUM1 as the normalization reference gene. b, Influenza virus PA and HA vRNAs relative expression. HeLa cells were transfected and infected as described above. vRNA levels were assessed by qPCR and normalized to PUM1 mRNA expression. c, Influenza virus production. Viral titers in the supernatant were quantified by plaque assay following infection of siRNA-transfected cells. All data represent the mean ± SEM (a, b) or ± s.d. (c) of three biological replicates. Genes with a fold change > 2 are indicated by patterned bars. Statistical analysis was performed using one-way ANOVA, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

Journal: bioRxiv

Article Title: Deep Learning-Driven Discovery of Mitochondrial Factors Modulating Influenza A Virus Infection

doi: 10.64898/2026.02.25.707858

Figure Lengend Snippet: a, IFN-βmRNA relative expression. HeLa cells were transfected with siRNAs targeting individual mitochondrial genes or a non-targeting control (siControl), followed by infection with influenza A virus. IFN-β mRNA levels were measured by quantitative PCR (qPCR), using PUM1 as the normalization reference gene. b, Influenza virus PA and HA vRNAs relative expression. HeLa cells were transfected and infected as described above. vRNA levels were assessed by qPCR and normalized to PUM1 mRNA expression. c, Influenza virus production. Viral titers in the supernatant were quantified by plaque assay following infection of siRNA-transfected cells. All data represent the mean ± SEM (a, b) or ± s.d. (c) of three biological replicates. Genes with a fold change > 2 are indicated by patterned bars. Statistical analysis was performed using one-way ANOVA, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

Article Snippet: The values were transformed to a linear scale and plotted on graphs. qPCR oligonucleotides for the knockdown of targeted genes were purchased from Bioneer.

Techniques: Expressing, Transfection, Control, Infection, Virus, Real-time Polymerase Chain Reaction, Plaque Assay