The selective translocation of molecules through membrane pores is an integral process in cells. We present a bacterial sugar transporter, CymA of unusual structural conformation due to a dynamic N terminus segment in the pore, reducing its diameter. We quantified the translocation kinetics of various cyclic sugars of different charge, size, and symmetry across native and truncated CymA devoid of the N terminus using singlechannel recordings. The chemically divergent cyclic hexasaccharides bind to the native and truncated pore with high affinity and translocate effectively. Specifically, these sugars bind and translocate rapidly through truncated CymA compared to native CymA. In contrast, larger cyclic heptasaccharides and octasaccharides do not translocate but bind to native and truncated CymA with distinct binding kinetics highlighting the importance of molecular charge, size and symmetry in translocation consistent with liposome assays. Based on the sugar-binding kinetics, we suggest that the N terminus most likely resides inside the native CymA barrel, regulating the transport rate of cyclic sugars. Finally, we present native CymA as a large nanopore sensor for the simultaneous single-molecule detection of various sugars at high resolution, establishing its functional versatility. This natural pore is expected to have several applications in nanobiotechnology and will help further our understanding of the fundamental mechanism of molecular transport.
Excitation‐emission matrix (EEM) has been extensively used as the comprehensive diagnostic tool to extract the biochemical fingerprint of the intrinsic fluorophores in a single scan window. However, there is a gap between the rigorous applications of the statistical tool with respect to discrimination of different stages of the disease which has been the subject for many years. Parallel factor analysis (PARAFAC) is one among the powerful statistical modeling approaches among others. In the present study, a total of 70 EEM matrices of normal, premalignant, and malignant oral tissues were given as a input, and seven intrinsic fluorophores were extracted as “components.” The extracted components were well correlated with respect to the appropriate excitation and emission spectral characteristics of the multiple intrinsic fluorophores such as tryptophan, flavin adenine dinucleotide (FAD), nicotinamide adenine dinucleotide (NADH), collagen‐1, porphyrin, tyrosine, and collagen. Subsequently, the student's t test and linear discriminant analysis (LDA) have been carried out with respect to the fluorescence intensity scores between normal vs. premalignant, normal vs. cancer, and premalignant vs. malignant groups. In normal vs. premalignant, all the seven fluorophores exhibit good statistical accuracy except porphyrin; normal vs. cancer exhibits higher statistical significance for tryptophan, NADH, and FAD than rest of the fluorophores, and premalignant vs. malignant shows proper classification in discriminating FAD, collagen‐1, and collagen. In summary, based on positive predictive value, the normal vs. premalignant exhibits 100% classification than the other two groups. Hence, the PARAFAC analysis could be the alternative and useful diagnostic tool in oral cancer diagnosis.
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