||Early and accurate diagnosis of infections is crucial for effective treatment and preventing the further spread of diseases. While single biomarkers have been used for diagnosis, they may lack sensitivity and specificity. Detection of multiple biomolecules can significantly enhance accuracy, reduce sample size and analysis time, and improve pathology screening. Hence, the development of a noninvasive biosensor that can simultaneously quantify multiple infection-related biomarkers, such as albumin proteins and bacterial molecules is particularly crucial. Herein, the synergistically developed biosensor uses a color-indicating optical sensor with gold nanoisland films (Au NIFs) covered with cholesteric liquid crystals (CLCs) as a precision biosensor. The CLC biosensor detection technique has the potential for biosensing due to the sensitive interfacial effects between the CLC molecules and AuNIF alignment. Alterations in the concentration of biomolecules lead to changes in the alignment power of the CLC-AuNIF interface, significantly modifying the hybrid plasmonic-photonic effect of the Au NIFs. CLCs-AuNIFs biosensor exhibited high sensitivity and accuracy in detecting concentrations of E. coli and albumin. The label-free limit of detection achieved was 1 × 106 CFU/ml for E. coli and 1 μg/ml for BSA. The proposed CLCs-AuNIFs biosensor was fast, visible, label-free, and color-indicating for detecting multiple molecules of microbes and albumin in different concentrations. The alteration of biomolecule concentrations demonstrated the alignment power changes on the interface, leading to the modification of hybrid plasmonic-photonic effect of Au NIFs. The potential applications of this development are vast, including biomedical, microbial, and industrial fields. The integrated biosensor can improve infection disease-related detection and quarantine, serving as a point-of-care. This development represents a pioneering study in the use of multiple biomarker detection in infection diagnosis and can have a significant impact on the future of infection diagnosis and treatment.