AI-Powered Western Blot Interpretation: A Novel Approach to Studying the Frameshift Mutant of Ubiquitin B (UBB+1) in Schizophrenia

Abstract

The application of artificial intelligence (AI) in the analysis of molecular biology data is becoming increasingly widespread. The Western Blot (WB) technique, a cornerstone in proteomic research, facilitates the identification and analysis of proteins, such as the frameshift mutant of ubiquitin B (UBB+1). In our study, we attempted to assess the potential of four different AI models—Gemini, Gemini Advanced, Microsoft Copilot, and ChatGPT 4—in the analysis of WB imagery containing UBB+1, derived from peripheral blood studies of patients suffering from schizophrenia. Participants, all male and diagnosed with schizophrenia, were recruited from the Specialist Psychiatric Care Team of Babinski Hospital in Lodz. After obtaining their informed consent, blood samples were collected and transported to the laboratory of the Department of Medical Biochemistry at the Medical University of Lodz. The samples were processed, synthesis of Ub-48UBB+1 dimers was performed, and the WB technique was applied. The result of the WB analysis, in the form of a photograph with basic labels but without a legend (JPG format), was implemented into ChatGPT 4, Microsoft Copilot, Gemini and Gemini Advanced. Following the implementation of the image, the command ‘Could you analyze the attached photo?’ was added, along with the protocol from Sample Preparation and Synthesis of Ub-48UBB+1 Dimers. The AI models effectively analyzed and interpreted WB images, with variations in their approaches and depth. Gemini excelled in detailing the WB process and biological significance of bands, while Gemini Advanced focused on specific band identification, especially Ub-48UBB+1 dimers. Microsoft Copilot provided a basic overview with less technicality, and ChatGPT 4 offered comprehensive band interpretations, linking them to patient samples and standards, thus confirming the hypothesis about the differing capabilities of these models. This discovery demonstrates the advanced capabilities of ChatGPT 4 and highlights the growing role of AI in scientific research, including the interpretation of results.