A Dual Fluorescence Turn-On Sensor Array Formed by Poly(para-aryleneethynylene) and Aggregation-Induced Emission Fluorophores for Sensitive Multiplexed Bacterial Recognition.

Bacterial infections have emerged as the leading causes of mortality and morbidity worldwide. Herein, we developed a dual-channel fluorescence "turn-on" sensor array, comprising six electrostatic complexes formed from one negatively charged poly(para-aryleneethynylene) (PPE) and six positively charged aggregation-induced emission (AIE) fluorophores. The 6-element array enabled the simultaneous identification of 20 bacteria (OD600=0.005) within 30s (99.0 % accuracy), demonstrating significant advantages over the array constituted by the 7 separate elements that constitute the complexes. Meanwhile, the array realized different mixing ratios and quantitative detection of prevalent bacteria associated with urinary tract infection (UTI). It also excelled in distinguishing six simulated bacteria samples in artificial urine. Remarkably, the limit of detection for E. coli and E. faecalis was notably low, at 0.000295 and 0.000329 (OD600), respectively. Finally, optimized by diverse machine learning algorithms, the designed array achieved 96.7 % accuracy in differentiating UTI clinical samples from healthy individuals using a random forest model, demonstrating the great potential for medical diagnostic applications.

Rapid identification of methicillin-resistant Staphylococcus aureus by MALDI-TOF MS: A meta-analysis.

Invasive infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are associated with high mortality and morbidity. The sooner the pathogen is determined, the better it is beneficial to patient. However, routine laboratory inspections are time-consuming and laborious. A thorough research was conducted in PubMed and Web of Science (until June 2021) to identify studies evaluating the accuracy of MRSA identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). STATA 15.0 software was used to analyze the pooled results of sensitivity, specificity, and 95% confidence intervals (CI). The summary receiver operating characteristic curves (SROC) and area under the curve (AUC) were utilized to show the overall performance of MALDI-TOF MS. Fifteen studies involving 2471 isolates were included in this study after the final selection in this meta-analysis. Using the random effects model forest plot to summarize the overall statistics, the sensitivity of MALDI-TOF MS for identifying MRSA was 92% (95% CI: 81%-97%), and the specificity was 97% (95% CI: 89%-99%). In the SROC curve, the AUC reached 0.99 (95% CI: 97%-99%). Deeks' test showed no significant publication bias in this meta-analysis. Compared with clinical reference methods, MALDI-TOF MS identification of MRSA shows a higher degree of sensitivity and specificity.

First preliminary study on identification of bacterial fish pathogens with Raman spectroscopy.

Accurate and rapid determination of bacterial disease agents of fish is an important step for sustainable and efficient aquaculture production. In general, biochemical and molecular methods are used for pathogen detection but they are usually time-consuming and required qualified personnel. Recently spectroscopic methods are preferred in clinical and food microbiology and declared as a promising alternative method for pathogens diagnosis with many advantages. In this study, the significant spectra of three important bacterial fish pathogens (Lactococcus garvieae, Vibrio anguillarum and Yersinia ruckeri) were determined by Raman spectroscopy. The first data of the pathogens were obtained and the distinctive differences in polysaccharides, nucleic acids, fatty acids and amino acids were identified. This preliminary study aimed to be pioneer for further studies in aquaculture and veterinary microbiology toward developing an alternative method for routine identification.

A review on machine learning-powered fluorescent and colorimetric sensor arrays for bacteria identification.

Biosensors have been widely used for bacteria determination with great success. However, the "lock-and-key" methodology used by biosensors to identify bacteria has a significant limitation: it can only detect one species of bacteria. In recent years, optical (fluorescent and colorimetric) sensor arrays are gradually gaining attention from researchers as a new type of biosensor. They can acquire multiple features of a target simultaneously, form a feature pattern, and determine the bacteria species with the help of pattern recognition/machine learning algorithms. Previous reviews in this area have focused on the interaction between the sensor array and bacteria or the materials used to make the sensors. This review, on the other hand, will provide researchers with a better understanding of the field by discussing fluorescent and colorimetric sensor arrays based on the mechanism of optical signal generation. These sensor arrays will be compared based on the identified species. Finally, we will discuss the limitations of these sensor arrays and explore possible solutions.

Identifying Clinically Relevant Bacteria Directly from Culture and Clinical Samples with a Handheld Mass Spectrometry Probe.

BACKGROUND: Rapid identification of bacteria is critical to prevent antimicrobial resistance and ensure positive patient outcomes. We have developed the MasSpec Pen, a handheld mass spectrometry-based device that enables rapid analysis of biological samples. Here, we evaluated the MasSpec Pen for identification of bacteria from culture and clinical samples. METHODS: A total of 247 molecular profiles were obtained from 43 well-characterized strains of 8 bacteria species that are clinically relevant to osteoarticular infections, including Staphylococcus aureus, Group A and B Streptococcus, and Kingella kingae, using the MasSpec Pen coupled to a high-resolution mass spectrometer. The molecular profiles were used to generate statistical classifiers based on metabolites that were predictive of Gram stain category, genus, and species. Then, we directly analyzed samples from 4 patients, including surgical specimens and clinical isolates, and used the classifiers to predict the etiologic agent. RESULTS: High accuracies were achieved for all levels of classification with a mean accuracy of 93.3% considering training and validation sets. Several biomolecules were detected at varied abundances between classes, many of which were selected as predictive features in the classifiers including glycerophospholipids and quorum-sensing molecules. The classifiers also enabled correct identification of Gram stain type and genus of the etiologic agent from 3 surgical specimens and all classification levels for clinical specimen isolates. CONCLUSIONS: The MasSpec Pen enables identification of several bacteria at different taxonomic levels in seconds from cultured samples and has potential for culture-independent identification of bacteria directly from clinical samples based on the detection of metabolic species.

Decision tree-based identification of Staphylococcus aureus via infrared spectral analysis of ambient gas.

In this study, eight types of bacteria were cultivated, including Staphylococcus aureus. The infrared absorption spectra of the gas surrounding cultured bacteria were recorded at a resolution of 0.5 cm-1 over the wavenumber range of 7500-500 cm-1. From these spectra, we searched for the infrared wavenumbers at which characteristic absorptions of the gas surrounding Staphylococcus aureus could be measured. This paper reports two wavenumber regions, 6516-6506 cm-1 and 2166-2158 cm-1. A decision tree-based machine learning algorithm was used to search for these wavenumber regions. The peak intensity or the absorbance difference was calculated for each region, and the ratio between them was obtained. When these ratios were used as training data, decision trees were created to classify the gas surrounding Staphylococcus aureus and the gas surrounding other bacteria into different groups. These decision trees show the potential effectiveness of using absorbance measurement at two wavenumber regions in finding Staphylococcus aureus.

"Omic" Approaches to Bacteria and Antibiotic Resistance Identification.

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of "-omics" approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Rapid in vitro differentiation of bacteria by ion mobility spectrometry.

Rapid screening of infected people plays a crucial role in interrupting infection chains. However, the current methods for identification of bacteria are very tedious and labor intense. Fast on-site screening for pathogens based on volatile organic compounds (VOCs) by ion mobility spectrometry (IMS) could help to differentiate between healthy and potentially infected subjects. As a first step towards this, the feasibility of differentiating between seven different bacteria including resistant strains was assessed using IMS coupled to multicapillary columns (MCC-IMS). The headspace above bacterial cultures was directly drawn and analyzed by MCC-IMS after 90 min of incubation. A cluster analysis software and statistical methods were applied to select discriminative VOC clusters. As a result, 63 VOC clusters were identified, enabling the differentiation between all investigated bacterial strains using canonical discriminant analysis. These 63 clusters were reduced to 7 discriminative VOC clusters by constructing a hierarchical classification tree. Using this tree, all bacteria including resistant strains could be classified with an AUC of 1.0 by receiver-operating characteristic analysis. In conclusion, MCC-IMS is able to differentiate the tested bacterial species, even the non-resistant and their corresponding resistant strains, based on VOC patterns after 90 min of cultivation. Although this result is very promising, in vivo studies need to be performed to investigate if this technology is able to also classify clinical samples. With a short analysis time of 5 min, MCC-IMS is quite attractive for a rapid screening for possible infections in various locations from hospitals to airports.Key Points• Differentiation of bacteria by MCC-IMS is shown after 90-min cultivation.• Non-resistant and resistant strains can be distinguished.• Classification of bacteria is possible based on metabolic features.

Development of the Correction Algorithm to Limit the Deformation of Bacterial Colonies Diffraction Patterns Caused by Misalignment and Its Impact on the Bacteria Identification in the Proposed Optical Biosensor.

Recently proposed methods of bacteria identification in optical biosensors based on the phenomenon of light diffraction on macro-colonies offer over 98% classification accuracy. However, such high accuracy relies on the comparable and repeatable spatial intensity distribution of diffraction patterns. Therefore, it is essential to eliminate all non-species/strain-dependent factors affecting the diffraction patterns. In this study, the impact of the bacterial colony and illuminating beam misalignment on the variation of classification features extracted from diffraction patterns was examined. It was demonstrated that misalignment introduced by the scanning module significantly affected diffraction patterns and extracted classification features used for bacteria identification. Therefore, it is a crucial system-dependent factor limiting the identification accuracy. The acceptable misalignment level, when the accuracy and quality of the classification features are not affected, was determined as no greater than 50 µm. Obtained results led to development of image-processing algorithms for determination of the direction of misalignment and concurrent alignment of the bacterial colonies' diffraction patterns. The proposed algorithms enable the rigorous monitoring and controlling of the measurement's conditions in order to preserve the high accuracy of bacteria identification.

Application of MALDI-TOF MS to rapid identification of anaerobic bacteria.

BACKGROUND: Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification. OBJECTIVE: To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes. METHODS: Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P-value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0. RESULTS: The identification accuracy of MALDI-TOF MS was 84% for species (I2 = 98.0%, P < 0.1), and 92% for genus (I2 = 96.6%, P < 0.1). Thereinto, the identification accuracy of Bacteroides was the highest at 96% with a 95% CI of 95-97%, followed by Lactobacillus spp., Parabacteroides spp., Clostridium spp., Propionibacterium spp., Prevotella spp., Veillonella spp. and Peptostreptococcus spp., and their correct identification rates were all above 90%, while the accuracy of rare anaerobic bacteria was relatively low. Meanwhile, the overall capabilities of two MALDI-TOF MS systems were different. The identification accuracy rate was 90% for VITEK MS vs. 86% for MALDI biotyper system. CONCLUSIONS: Our research showed that MALDI-TOF-MS was satisfactory in genus identification of clinical pathogenic anaerobic bacteria. However, this method still suffers from different drawbacks in precise identification of rare anaerobe and species levels of common anaerobic bacteria.

GC-IMS headspace analyses allow early recognition of bacterial growth and rapid pathogen differentiation in standard blood cultures.

Outcome of patients with blood stream infections (BSI) depends on the rapid initiation of adequate antibiotic therapy, which relies on the fast and reliable identification of the underlying pathogen. Blood cultures (BC) using CO2-sensitive colorimetric indicators and subsequent microbiological culturing are the diagnostic gold standard but turnaround times range between 24 and 48 h. The detection of volatile organic compounds of microbial origin (mVOC) has been described as a feasible method for identifying microbial growth and to differentiate between several microbial species. In this study, we aimed to investigate the ability of mVOC analyses using a gas chromatograph coupled to an ion mobility spectrometer (GC-IMS) for the recognition of bacterial growth and bacterial differentiation in BCs. Therefore, samples of whole blood and diluted bacterial suspension were injected into aerobic and anaerobic BC bottles and incubated for 8 h. Headspace samples from cultures of Escherichia coli (DSM 25944), Staphylococcus aureus (DSM 13661), and Pseudomonas aeruginosa (DSM 1117) were investigated hourly and we determined at which point of time a differentiation between the bacteria was possible. We found specific mVOC signals in the headspace over growing BCs of all three bacterial species. GC-IMS headspace analyses allowed faster recognition of bacterial growth than the colorimetric indicator of the BCs. A differentiation between the three investigated species was possible after 6 h of incubation with a high reliability in the principal component analysis. We concluded that GC-IMS headspace analyses could be a helpful method for the rapid detection and identification of bacteria in BSI.

Fluorescent nanodiamond-bacteriophage conjugates maintain host specificity.

Rapid identification of specific bacterial strains within clinical, environmental, and food samples can facilitate the prevention and treatment of disease. Fluorescent nanodiamonds (FNDs) are being developed as biomarkers in biology and medicine, due to their excellent imaging properties, ability to accept surface modifications, and lack of toxicity. Bacteriophages, the viruses of bacteria, can have exquisite specificity for certain hosts. We propose to exploit the properties of FNDs and phages to develop phages conjugated with FNDs as long-lived fluorescent diagnostic reagents. In this study, we develop a simple procedure to create such fluorescent probes by functionalizing the FNDs and phages with streptavidin and biotin, respectively. We find that the FND-phage conjugates retain the favorable characteristics of the individual components and can discern their proper host within a mixture. This technology may be further explored using different phage/bacteria systems, different FND color centers and alternate chemical labeling schemes for additional means of bacterial identification and new single-cell/virus studies.

Strain-level typing and identification of bacteria - a novel approach for SERS active plasmonic nanostructures.

One of the potential applications of surface-enhanced Raman spectroscopy (SERS) is the detection of biological compounds and microorganisms. Here we demonstrate that SERS coupled with principal component analysis (PCA) serves as a perfect method for determining the taxonomic affiliation of bacteria at the strain level. We demonstrate for the first time that it is possible to distinguish different genoserogroups within a single species, Listeria monocytogenes, which is one of the most virulent foodborne pathogens and in some cases contact with which may be fatal. We also postulate that it is possible to detect additional proteins in the L. monocytogenes cell envelope, which provide resistance to benzalkonium chloride and cadmium. A better understanding of this infectious agent could help in selecting the appropriate pharmaceutical product for enhanced treatment. Graphical abstract ᅟ.

Influence of meteorological factors on the level and characteristics of culturable bacteria in the air in Gliwice, Upper Silesia (Poland).

Numerous studies have focused on occupational and indoor environments because people spend more than 90% of their time in them. Nevertheless, air is the main source of bacteria in indoors, and outdoor exposure is also crucial. Worldwide studies have indicated that bacterial concentrations vary among different types of outdoor environments, with considerable seasonal variations as well. Conducting comprehensive monitoring of atmospheric aerosol concentrations is very important not only for environmental management but also for the assessment of the health impacts of air pollution. To our knowledge, this is the first study to present outdoor and seasonal changes of bioaerosol data regarding an urban area of Poland. This study aimed to characterize culturable bacteria populations present in outdoor air in Gliwice, Upper Silesia Region, Poland, over the course of four seasons (spring, summer, autumn and winter) through quantification and identification procedures. In this study, the samples of bioaerosol were collected using a six-stage Andersen cascade impactor (with aerodynamic cut-off diameters of 7.0, 4.7, 3.3, 2.1, 1.1 and 0.65 µm). Results showed that the concentration of airborne bacteria ranged from 4 CFU m-3, measured on one winter day, to a maximum equal to 669 CFU m-3 on a spring day. The average size of culturable bacterial aerosol over the study period was 199 CFU m-3. The maximal seasonally averaged concentration was found in the spring season and reached 306 CFU m-3, and the minimal seasonally averaged concentration was found in the winter 49 CFU m-3. The most prevalent bacteria found outdoors were gram-positive rods that form endospores. Statistically, the most important meteorological factors related to the viability of airborne bacteria were temperature and UV radiation. These results may contribute to the promotion and implementation of preventative public health programmes and the formulation of recommendations aimed at providing healthier outdoor environments.

Bacteriological Assessment of Pneumonia Caused by Gram-Negative Bacteria in Patients Hospitalized in Intensive Care Unit.

The article presents the results of 11-year study (2005-2015) of Gram-negative bacteria responsible for pneumonia in 2033 mechanically ventilated patients hospitalized in Intensive Care Unit. Of 8796 biological samples, consisting mainly of bronchial aspirate (97.9 %), 2056 bacterial strains were isolated and subjected to identification. VITEK 2 was used to determine drug susceptibility (classified according to the EUCAST criteria). ESBL, MBL and KPC-producing strains were identified by means of phenotypic methods using appropriate discs. The findings were that the predominant bacteria responsible for infections consisted of Enterobacteriaceae (42.0 %), Acinetobacter baumannii (37.2 %), Pseudomonas aeruginosa (16.1 %), and Stenotrophomonas maltophila (4.7 %). We observed a rise in the number of bacteria causing pneumonia throughout the study period, especially in S. maltophila and Enterobacteriaceae ESBL (+). Gram-negative bacilli were 100 % susceptible to colistin, apart from naturally resistant strains such as Proteus mirabilis, Serratia marcescens, whereas Enterobacteriaceae ESBL (+) were susceptible to imipenem and meropenem. Acinetobacter baumannii strains exhibited the lowest drug susceptibility. In conclusion, we report an increase in the prevalence of pneumonia associated with Gram-negative bacteria in mechanically ventilated intensive care patients. Colistin remains the most effective drug against the majority of Gram-negative bacteria. Therapeutic problems are common in the course of treatment of Acinetobacter baumannii infections.

Medicago truncatula Gaertn. as a model for understanding the mechanism of growth promotion by bacteria from rhizosphere and nodules of alfalfa.

MAIN CONCLUSION: The present study showed all the 16 strains isolated and identified from the alfalfa rhizosphere and nodules, and registered in GenBank, to be good candidates for targeted use in studies addressing the rather weak known mechanism of plant growth promotion, including that of Medicago truncatula, a molecular crop model. Based on physiological, biochemical and molecular analysis, the 16 isolates obtained were ascribed to the following five families: Bacillaceae, Rhizobiaceae, Xantomonadaceae, Enterobacteriaceae and Pseudomonadaceae, within which 9 genera and 16 species were identified. All these bacteria were found to significantly enhance fresh and dry weight of root, shoots and whole 5-week-old seedlings. The bacteria were capable of the in vitro use of tryptophan to produce indolic compounds at various concentrations. The ability of almost all the strains to enhance growth of seedlings and individual roots was positively correlated with the production of the indolic compounds (r = 0.69; P = 0.0001), but not with the 1-aminocyclopropane-1-carboxylate deaminase (ACCD) activity (no correlation). For some strains, it was difficult to conclude whether the growth promotion was related to the production of indolic compounds or to the ACCD activity. It is likely that promotion of M. truncatula root development involves also root interaction with pseudomonads, known to produce 2,4-diacetylphloroglucinol (DAPG), a secondary metabolite reported to alter the root architecture by interacting with an auxin-dependent signaling pathway. Inoculation of seedlings with Pseudomonas brassicacearum KK 5, a bacterium known for its lowest ability to produce indolic compounds, the highest ACCD activity and the presence of the phlD gene responsible for DAPG precursor synthesis, resulted in a substantial promotion of root development. Inoculation with the strain increased the endogenous IAA level in M. truncatula leaves after inoculation of 5-week-old seedlings. Three other strains examined in this study also increased the IAA level in the leaves upon inoculation. Moreover, several other factors such as mobilization of phosphorus and zinc to make them available to plants, iron sequestration by siderophore production and the ability to ammonia production also contributed substantially to the phytostimulatory biofertilizing potential of isolated strains. There is, thus, evidence that Medicago truncatula growth promotion by rhizobacteria involves more than one mechanism.

Direct Identification of Aerobic Bacteria by Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Is Accurate and Robust.

BACKGROUND: Bacterial identification in the clinical laboratory can be laborious and expensive. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a rapid and cost-effective diagnostic tool for the identification of organisms routinely found in the microbiology laboratory. The objective of this study was to demonstrate that identification of aerobic Gram-positive and Gram-negative organisms could be performed accurately and efficiently by MALDI-TOF MS and the Bruker Biotyper system without the use of time-consuming extraction methodologies. METHODS: Isolates previously recovered by routine culture and workup from clinical specimens were cultured to appropriate media, identified directly by MALDI-TOF MS, and compared to results from various biochemical identification methods. RESULTS: Using the direct-smear method, 99.5% and 98.0% of aerobic Gram-negative and Gram-positive bacteria, respectively, were identified to the genus level. At a score of ≥1.9, 97.6% Gram-negative organisms and 94.6% Gram-positive organisms were correctly identified to the species level by direct-smear method. Only 1.1% of isolates required further reflex to direct-plate extraction. The direct-smear method proved to be robust, as various growth temperatures, media, culture age, and different operators had no notable impact on the bacterial identification rate. CONCLUSION: The direct-smear method is an accurate and time-saving method for routine species-level bacterial identification.

MetaBIDx: a new computational approach to bacteria identification in microbiomes.

Objectives: This study introduces MetaBIDx, a computational method designed to enhance species prediction in metagenomic environments. The method addresses the challenge of accurate species identification in complex microbiomes, which is due to the large number of generated reads and the ever-expanding number of bacterial genomes. Bacterial identification is essential for disease diagnosis and tracing outbreaks associated with microbial infections. Methods: MetaBIDx utilizes a modified Bloom filter for efficient indexing of reference genomes and incorporates a novel strategy for reducing false positives by clustering species based on their genomic coverages by identified reads. The approach was evaluated and compared with several well-established tools across various datasets. Precision, recall, and F1-score were used to quantify the accuracy of species prediction. Results: MetaBIDx demonstrated superior performance compared to other tools, especially in terms of precision and F1-score. The application of clustering based on approximate coverages significantly improved precision in species identification, effectively minimizing false positives. We further demonstrated that other methods can also benefit from our approach to removing false positives by clustering species based on approximate coverages. Conclusion: With a novel approach to reducing false positives and the effective use of a modified Bloom filter to index species, MetaBIDx represents an advancement in metagenomic analysis. The findings suggest that the proposed approach could also benefit other metagenomic tools, indicating its potential for broader application in the field. The study lays the groundwork for future improvements in computational efficiency and the expansion of microbial databases.

Use of Matrix-Assisted and Laser Desorption/Ionization Time-of-Flight Technology in the Identification of Aeromonas Strains Isolated from Retail Sushi and Sashimi.

The genus Aeromonas includes well-known pathogenic species for fishes and humans that are widely distributed in the aquatic environment and foods. Nowadays, one of the main issues related to wild Aeromonas isolates is their identification at the species level, which is challenging using classical microbiological and biomolecular methods. This study aims to test MALDI-TOF MS technology in the identification of Aeromonas strains isolated from n. 60 retail sushi and sashimi boxes using an implemented version of the SARAMIS software V4.12. A total of 43 certified Aeromonas strains were used to implement the SARAMIS database by importing the spectra obtained from their identification. The original SARAMIS version (V4.12) failed to recognize 62.79% of the certified strains, while the herein-implemented version (V4.12plus) allowed the identification of all the certified strains at least to the genus level with a match of no less than 85%. Regarding the sushi and sashimi samples, Aeromonas spp. was detected in n. 18 (30%) boxes. A total of 127 colonies were identified at the species level, with A. salmonicida detected as the most prevalent species, followed by A. bestiarum and A. caviae. Based on the results of the present study, we could speculate that MALDI-TOF technology could be a useful tool both for the food industry to monitor product contamination and for clinical purposes to make diagnoses effectively and quickly.

Molecular engineering of thiophene- and pyrrole-fused core arylamine systems: Tuning redox properties, NIR spectral responsiveness and bacterial imaging applications.

The thiophene- and pyrrole-fused heterocyclic compounds have garnered significant interest for their distinctive electron-rich characteristics and notable optoelectronic properties. However, the construction of high-performance systems within this class is of great challenge. Herein, we develop a series of novel dithieno[3,2-b:2',3'-d] pyrrole (DTP) and tetrathieno[3,2-b:2',3'-d] pyrrole (TTP) bridged arylamine compounds (DTP-C4, DTP-C12, DTP-C4-Fc, TTP-C4-OMe, TTP-C4, and TTP-C12) with varying carbon chain lengths. The pertinent experimental results reveal that this series of compounds undergo completely reversible multistep redox processes. Notably, TTP-bridged compounds TTP-C4 and TTP-C12 exhibit impressive multistep near-infrared (NIR) absorption alterations with notable color changes and electroluminescent behaviors, which are mainly attributed to the charge transfer transitions from terminal arylamine units to central bridges, as supported by theoretical calculations. Additionally, compound DTP-C4 demonstrates the ability to visually identify gram-positive and gram-negative bacteria. Therefore, this work suggests the promising electroresponsive nature of compounds TTP-C4 and TTP-C12, positioning them as excellent materials for various applications. It also provides a facile approach to constructing high-performance multifunctional luminescent materials, particularly those with strong and long-wavelength NIR absorption capabilities.