Biosensing of multiple aromatic xenobiotics in water by in-house fabricated prototype device.

Portable, low-cost, and accurate monitoring of hazardous mono-aromatic pollutants, such as phenol or benzene group of compounds in water is a challenging task due to the lack of suitable detectable functional groups and complex matrix of environmental samples. Here, we use a series of protein-based biosensing recognition scaffolds to enable specific detection of several mono-aromatic classes of xenobiotics. The biosensor is tuned to perform in intricate environmental conditions and is interfaced with an in-house manufactured, multi-channel device (AroTrack) capable of direct and sensitive detection of several of these aromatic contaminants, such as phenol, benzene, and 2,3-dimethylphenol (2,3-DMP) in the low ppb range (10-200 ppb). The efficiency of the prototype device was benchmarked in both simulated wastewater and real environmental samples comprising 10 times higher isostructural aromatic pollutants or ions. It was established that AroTrack is reliable for environmental sample testing with a high degree of reproducibility and efficiency comparable to that of modern spectrophotometers (<5 % error). The battery-operated device costs less than $50 to fabricate and this low cost makes it effective to be implemented in rural and low-income settings which suggests immense field deployable potential.

Ultrasensitive detection of aromatic water pollutants through protein immobilization driven organic electrochemical transistors.

Xenobiotic aromatic water pollutants pose an extreme threat to environmental sustainability. Due to the lack of detectable functional groups in these compounds and scarcity of selective bio-recognition scaffolds, easy-to-use sensing strategies capable of on-site detection remain unavailable. Herein, to address this lacune, we entail a strategy that combines biosensor scaffolds with organic electronics to create a compact device for environmental aromatic pollution monitoring. As proof of principle, a sensor module capable of rapid, economic, reliable, and ultrasensitive detection of phenol down to 2 ppb (0.02 µM) was designed wherein biosensing protein MopR was coupled with an organic electrochemical transistor (OECT). For effective interfacing of the sensing scaffold MopR, graphene oxide (GO) nanosheets were optimized as a host immobilization matrix. The MopR-GO immobilized sensor module was subsequently substituted as the gate electrode with PEDOT:PSS serving as an organic semiconductor material. The resulting OECT sensor provided a favourable microenvironment for protein activity, maintaining high specificity. Exclusive phenol detection with minimal loss of sensitivity (<5% error) could be achieved in both complex pollutant mixtures and real environmental samples. This fabrication strategy that amalgamates biological biosensors with organic electronics harnesses the potential to achieve detection of a host of emerging pollutants.

Identifying Selectivity Filters in Protein Biosensor for Ligand Screening.

Specialized sensing mechanisms in bacteria enable the identification of cognate ligands with remarkable selectivity in highly xenobiotic-polluted environments where these ligands are utilized as energy sources. Here, via integrating all-atom computer simulation, biochemical assay, and isothermal titration calorimetry measurements, we determine the molecular basis of MopR, a phenol biosensor's complex selection process of ligand entry. Our results reveal a set of strategically placed selectivity filters along the ligand entry pathway of MopR. These filters act as checkpoints, screening diverse aromatic ligands at the protein surface based on their chemical features and sizes. Ligands meeting specific criteria are allowed to enter the sensing site in an orientation-dependent manner. Sequence and structural analyses demonstrate the conservation of this ligand entry mechanism across the sensor class, with individual amino acids along the selectivity filter path playing a critical role in ligand selection. Together, this investigation highlights the importance of interactions with the ligand entry pathway, in addition to interactions within the binding pocket, in achieving ligand selectivity in biological sensing. The findings enhance our understanding of ligand selectivity in bacterial phenol biosensors and provide insights for rational expansion of the biosensor repertoire, particularly for the biotechnologically relevant class of aromatic pollutants.

Intrinsic proclivity of left-handed conformation in large Nest motif peptides inferred from molecular dynamics.

The 'Nest' motif plays a functional role in protein owing to its ligand binding potential aided by geometric concavity. The presence of less favored left-handed conformation (L-state) in its structure makes this concavity possible and in shaping the native chemical environment amenable to stable binding interactions. To understand the persistent appearance of L-state torsion in the Nest motif, we analyzed 0.5µs Molecular Dynamics (MD) simulation trajectories of 35 six-residue peptides (out of a total of 50 large Nest sequences of ≥6 residues) identified in our previous study. Analysis of the MD trajectories of the individual peptides reveals initial L-state in 60% of the peptides persists for >40% of the trajectory. Further, Nests with different sequences appear to adopt a specific conformational state driven by the neighboring L-state residues. The sequences also possess short secondary structures and amino acid repeats, suggesting evolutionary conservation and the specific role of amino acids in locally predisposing the torsion angle to the L-state. These findings help us to understand how L-state conformation is an essential prerequisite in stabilizing the Nest motif and shed light on the sequence-structure-function paradigm in the rational design of peptides and peptidomimetics for therapeutics.Communicated by Ramaswamy H. Sarma.

Harnessing the Potential of Biological Recognition Elements for Water Pollution Monitoring.

Environmental monitoring of pollutants is an imperative first step to remove the genotoxic, embryotoxic, and carcinogenic toxins. Various biological sensing elements such as proteins, aptamers, whole cells, etc., have been used to track down major pollutants, including heavy metals, aromatic pollutants, pathogenic microorganisms, and pesticides in both environmental samples and drinking water, demonstrating their potential in a true sense. The intermixed use of nanomaterials, electronics, and microfluidic systems has further improved the design and enabled robust on-site detection with enhanced sensitivity. Through this perspective, we shed light on the advances in the field and entail recent efforts to optimize these systems for real-time, online sensing and on-site field monitoring.

Rhino-Orbito-Cerebral Mucormycosis During the Second Wave of Covid-19: The Indian Scenario.

Mucormycosis is a life threatening, opportunistic infection often seen in individuals with a weak immune system. With an upsurge of cases of Covid-19, a drastic increase in cases of Rhino-Orbito-Cerebral Mucormycosis is being witnessed at present. This article has been written with the purpose of understanding the factors responsible for it and the challenges it brings along for the Indian health-care system at present. Possible solutions for dealing with these problems have also been included in the manuscript. Google, PubMed and ENT Cochrane databases were searched without a time limit using key words like "Mucormycosis", "Rhino-cerebral-mucormycosis" in conjunction with "COVID-19" and "SARS CoV-2". We found 34 articles to be relevant and hence included them to write this review. Rhino-Orbito-Cerebral Mucormycosis is being seen due to coming together of the three entities-the agent, host and environment that constitute the epidemiological triad for this disease in India. Responsible factors are uncontrolled diabetes mellitus, overzealous use of steroids and antibiotics and other environment related issues. The solutions for these problems lie in spreading awareness about prevention of these practices along with early diagnosis and treatment of mucormycosis. To deal effectively with this situation, particularly when there is an existing overload on otolaryngologists and the rest of the health-care system, a multipronged and multilevel collaborative approach is the need of the hour. With effective Standard Operating Procedures and guidelines promoting a multidisciplinary approach for early diagnosis and treatment, we can surely overcome this situation.

New facets of larger Nest motifs in proteins.

The Nest is a concave-shaped structural motif in proteins formed by consecutive enantiomeric left-handed (L) and right-handed (R) helical conformation of the backbone. This important motif subsumes many turn and helix capping structures and binds electron-rich ligands. Simple Nests are either RL or LR. Larger Nests (>2 residues long) may be RLR, LRL, RLRL, and so forth, being considered as composed of overlapping simple Nests. The larger Nests remain under-explored despite their widely known contributions to protein function. In our study, we address whether the recurrence of enantiomeric geometry in the larger Nests constrains the peptide backbone such that distinct compositional and conformational preferences are seen compared to simple Nests. Our analysis reveals the critical role of the L helical torsion angle in the formation of larger Nests. This can be observed through the higher propensity of residue or secondary structure combinations in LR and LRL backbone conformation in comparison to RL or RLR, although LR/LRL is considerably lower by occurrence. We also find that the most abundant doublets and triplets in Nests have a propensity for particular secondary structures, suggesting a strong sequence-structure relationship in the larger Nest. Overall, our analysis corroborates distinct features of simple and the larger Nests. Such insights would be helpful towards in-vitro design of peptides and peptidomimetic studies.

Interaction landscape of a 'CαNN' motif with arsenate and arsenite: a potential peptide-based scavenger of arsenic.

Arsenic (As) is a toxic metalloid that has drawn immense attention from the scientific community recently due to its fatal effects through its unwanted occurrence in ground water around the globe. The presence of an excess amount of water soluble arsenate and/or arsenite salt (permissible limit 10 µg L-1 as recommended by the WHO) in water has been correlated with several human diseases. Although arsenate (HAsO4 2-) is a molecular analogue of phosphate (HPO4 2-), phosphate is indispensable for life, while arsenic and its salts are toxic. Therefore, it is worthwhile to focus on the removal of arsenic from water. Towards this end, the design of peptide-based scaffolds for the recognition of arsenate and arsenite would add a new dimension. Utilizing the stereochemical similarity between arsenate (HAsO4 2-) and phosphate (HPO4 2-), we successfully investigated the recognition of arsenate and arsenite with a naturally occurring novel phosphate binding 'CαNN' motif and its related designed analogues. Using computational as well as biophysical approaches, for the first time, we report here that a designed peptide-based scaffold based on the 'CαNN' motif can recognize anions of arsenic in a thermodynamically favorable manner in a context-free system. This peptide-based arsenic binding agent has the potential for future development as a scavenger of arsenic anions to obtain arsenic free water.

Design of Ultrasensitive Protein Biosensor Strips for Selective Detection of Aromatic Contaminants in Environmental Wastewater.

Phenol and its derivatives constitute a class of highly toxic xenobiotics that pollute both river and groundwater. Here, we use a highly stable enzyme-based in vitro biosensing scaffold to develop a chip-based environmental diagnostic for in situ accurate, direct detection of phenol with selectively down to 10 ppb. Mesoporous silica nanoparticles (MCM41) having a pore diameter of 6.5 nm was screened and found to be the optimal solid support for creation of a robust immobilized protein based sensor, which retains stability, enzyme activity, sensitivity, and selectivity at par with solution format. The sensor strip exhibits minimal cross reactivity in simulated wastewater, crowded with several common pollutants. Moreover, this design is competent towards detection of phenol content with 95% accuracy in real-time environmental samples collected from local surroundings, making it a viable candidate for commercialization. The enzyme has been further modified via evolution driven mutagenesis to generate an exclusive 2,3-dimethylphenol sensor with equivalent selectivity and sensitivity as the native phenol sensor. Thus, this approach can be extended to generate a battery of sensors for other priority aromatic pollutants, highlighting the versatility of the biosensor unit. This novel biosensor design presents promising potential for direct detection and can be integrated in a device format for on-site pollutant monitoring.