Smartphone Imaging Device for Multimodal Detection of Hydrogen Sulfide Using Cu-Doped MOF Sensors.

Multimodal sensing platforms may offer reliable, fast results, but it is still challenging to incorporate biosensors with high discriminating ability in complex biological samples. Herein, we established a highly sensitive dual colorimetric/electrochemical monitoring approach for the detection of hydrogen sulfide (H2S) utilizing Cu-doped In-based metal-organic frameworks (Cu/In-MOFs) combined with a versatile color selector software-based smartphone imaging device. H2S can result in the enhancement of the electrochemical signal because of the electroactive substance copper sulfide (CuxS), the decrease of the colorimetric signal of the characteristic absorption response caused by the strong coordination effect on Cu/In-MOFs, and the obvious changes of red-green-blue (RGB) values of images acquired via an intelligent smartphone. Attractively, the Cu/In-MOFs-based multimodal detection guarantees precise and sensitive detection of H2S with triple-signal detection limits of 0.096 µM (electrochemical signals), 0.098 µM (colorimetric signals), and 0.099 µM (smartphone signals) and an outstanding linear response. This analytical toolkit provides an idea for fabricating a robust, sensitive, tolerant matrix and reliable sensing platform for rapidly monitoring H2S in clinical disease diagnosis and visual supervision.

Electrochemical sensor for hydrogen sulfide detection using electrocatalysis-assisted amplification and chemical reaction-mediated signal enhancement.

An ultrasensitive electrochemical biosensing platform has been designed by combining electrocatalysis-assisted H2S amplification with a chemical reaction-mediated electrochemical signal-boosted system for H2S detection based on Cu-Mn(OH)2 hexagonal nanorings. The signal amplification is initiated by an electrocatalysis reaction that can grasp specific H2S substrates and further highly amplify electrochemical signals. Then, the unique chemical reaction is powered by copper ion and generates a large amount of electroactive CuxS products on the electrode surface, thus achieving the multiple amplification of H2S detection. Finally, the Cu-Mn(OH)2 loaded with plenty of electroactive CuxS can be captured on the electrode for further improving the electrochemical signal thus obtaining ultra-high sensitive determination of H2S. The established electrochemical biosensing platform displays a wide analytical range of 0.1 µM to 265 µM with a low detection limit of 0.096 µM. The satisfactory selectivity allows the electrochemical sensor to distinguish H2S from other interfering substances without any complicated pretreatment, even in complex tumor cell samples. Thus, our designed electrocatalysis-assisted amplification strategy offers a powerful analysis toolkit for the early determination of H2S-related disease in clinical diagnosis.

Genome-Wide Identification and Characterization of Potato Long Non-coding RNAs Associated With Phytophthora infestans Resistance.

Long non-coding RNA (lncRNA) is a crucial regulatory mechanism in the plant response to biotic and abiotic stress. However, their roles in potato (Solanum tuberosum L.) resistance to Phytophthora infestans (P. infestans) largely remain unknown. In this study, we identify 2857 lncRNAs and 33,150 mRNAs of the potato from large-scale published RNA sequencing data. Characteristic analysis indicates a similar distribution pattern of lncRNAs and mRNAs on the potato chromosomes, and the mRNAs were longer and had more exons than lncRNAs. Identification of alternative splicing (AS) shows that there were a total of 2491 lncRNAs generated from AS and the highest frequency (46.49%) of alternative acceptors (AA). We performed R package TCseq to cluster 133 specific differentially expressed lncRNAs from resistance lines and found that the lncRNAs of cluster 2 were upregulated. The lncRNA targets were subject to KEGG pathway enrichment analysis, and the interactive network between lncRNAs and mRNAs was constructed by using GENIE3, a random forest machine learning algorithm. Transient overexpression of StLNC0004 in Nicotiana benthamiana significantly suppresses P. infestans growth compared with a control, and the expression of extensin (NbEXT), the ortholog of the StLNC0004 target gene, was significantly upregulated in the overexpression line. Together, these results suggest that lncRNAs play potential functional roles in the potato response to P. infestans infection.