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Artificial Intelligence (AI) has great potential in diverse real-time mission-critical applications and one such application is telesurgery or robotic surgery. However, some issues like security, throughput, reliability, trust, and transparency are still challenging in an AI-enabled telesurgery system. Motivated from these challenges, in this paper, we propose a blockchain and AI-empowered telesurgery system towards 6G called BATS, which is a self-manageable, secure, transparent, and trustable system with massive Ultra-Reliable Low-Latency Communication (mURLLC). BATS uses AI algorithms such as eXtreme Gradient Boosting (XGBoost) to classify the disease with their criticality score ranging from 0 to 1. Moreover, BATS uses UAVs to transport light-weight healthcare items such as medicines and surgical tools in an emergent situation (during surgical procedures) to avoid the road-traffic congestions.Results show that BATS achieves better prediction accuracy, high throughput when the number of users increases, extremely low packet loss ratio, low storage cost, high mining profit, and low bandwidth consumption by nterPlanetary File System (IPFS) compared to the traditional schemes.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 or COVID-19), outbreak was first reported in December 2019 in the Wuhan, China. COVID-19 managed to spread worldwide and so far more than 9.1 million cases and more than 4.7 lakh death has been reported globally. Children, pregnant women, elderly population, immunocompromised patients, and patients with conditions like asthma, diabetes, etc. are highly vulnerable to COVID infection. Currently, there is no treatment available for COVID-19 infection. Traditional medicinal plants have provided bioactive molecules in the past that are efficiently used during conditions like cancer, malaria, microbial infections, immune-compromised states, etc. AYUSH India has recommended the use of Curcuma longa, Allium sativum, Ocimum tenuiflorum, and Withania somnifera for immune-boosting during SARS-CoV-2 infection. In the present study, we investigated the potential of 63-major bioactive molecules of these plants against SARS-CoV-2 main protease (Mpro) through docking studies and compared the results with known inhibitor 11a. Our results proposed cuscohygrine, γ-Glutamyl-S-allylcysteine, anahygrine, and S-allylcystein as the potent inhibitors against Mpro identified using molecular docking and molecular simulation dynamics. Interestingly, these molecules are from A. sativum, and W. somnifera, which are known for their antimicrobial and immunomodulatory potential. None of the proposed molecules have earlier been reported as antiviral molecules. Our results predict very strong potential of these four-molecules against SARS-CoV-2 Mpro, especially γ-glutamyl-S-allylcysteine, as all four form hydrogen bonding with Glu166 that is a crucial residue for the formation of the biologically active dimeric form of Mpro. Therefore, we strongly recommend further research on these biomolecules against SARS-CoV-2.

It is the acquisition of unique traits that adds to the enigma of microbial capabilities to carry out extraordinary processes. One such ecosystem is the soil exposed to radionuclides, in the vicinity of atomic power stations. With the aim to study thorium (Th) tolerance in the indigenous bacteria of such soil, the bacteria were isolated and screened for maximum thorium tolerance. Out of all, only one strain AM3, found to tolerate extraordinary levels of Th (1500 mg L−1), was identified to be belonging to genus Providencia and showed maximum genetic similarity with the type strain P. vermicola OP1T. This is the first report suggesting any bacteria to tolerate such high Th and we propose to term such microbes as ‘thoriotolerant’. The medium composition for cultivating AM3 was optimized using response surface methodology (RSM) which also led to an improvement in its Th-tolerance capabilities by 23%. AM3 was found to be a good producer of EPS and hence one component study was also employed for its optimization. Moreover, the EPS produced by the strain showed interaction with Th, which was deduced by Fourier Transform Infrared (FTIR) spectroscopy.

Polyhydroxyalkanoates (PHAs) are bio-polyesters of hydroxyalkanoates that accumulate intracellularly in case of prokaryotes, as cytoplasmic granules, under carbon rich and paucity of nitrogen, phosphorous, sulphur and oxygen where it can serve as carbon and energy source under nutrient limiting condition and/or environmental stress conditions. In adverse growth conditions, many bacteria have ability to store nutrients in form of PHA granules using their specific metabolic pathways during stationary growth phase, in the presence of high levels of carbon containing nutrient sources. Bacterial PHAs have generated attention as an alternative to petroleum derived synthetic plastics. It possesses the characteristic physico-chemical properties comparable to the synthetic plastics. These properties of PHAs can be improved by blending of PHAs with other natural polymer like starch, cellulose and semisynthetic polymers like poly lactic acids and polycaprolactones. Being eco-friendly, biodegradable and biocompatible; major PHAs such as, Polyhydroxybutyrate (PHB) and Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) have found numerous vital applications in pharmaceutical, biomedical, textile, cosmetic, agricultural, treatment of waste water and have been successfully employed for Food packaging industries. This review provides a comprehensive knowledge about the world of PHAs covering its major aspects, namely its chemical nature and structure, biosynthesis, various methods of screening of potential PHA producing bacteria along with properties, several techniques used for its recovery and further characterization.

Microbes possess a tremendous potential to interact with their surroundings and have continued to shape the future of all life forms existing on earth. Of all the groups of microbes, viruses are the most nefarious creatures which cannot be solely classified as living or non-living but still pose the greatest threats to the biosphere. Viruses are minuscule, diverse and are probably the only entities that exhibit non-mutualistic association with other lifeforms while retaining their ability to infect and hijack any of the existing living being on the planet. The latest global devastation, caused by novel SARS-CoV-2, is unparalleled in the last century. This review encompasses the mysterious origin of this virus by tracking its lineage, which may help to decode the conundrum of SARS-CoV-2 and shed more light on its epidemiology. The implications and the challenge posed by this virus to the scientific community to the medical community and the economy at large are reflected. Also discussed is the paradigm shift brought upon by the COVID-19 pandemic on the human psyche and their behaviour. Graphic Abstract

Peptide Nucleic Acid (PNA) serves as an artificial functional analog of DNA. Being immune to enzymatic degradation and possessing strong affinity towards DNA and RNA, it is an ideal candidate for many medical and biotechnological applications that are of antisense and antigene in nature. PNAs are anticipated to have its application in DNA and RNA detection as well as quantification, to serve as antibacterial and antiviral agents, and silencing gene for developing anticancer strategies. Although, their restricted entry in both eukaryotic and prokaryotic cells limit their applications. In addition, aggregation of PNA in storage containers reduces the quality and quantity of functional PNA that makes it inadequate for their mass production and storage. To overcome these limitations, researchers have modified PNA either by the addition of diverse functional groups at various loci on its backbone, or by synthesizing chimeras with other moieties associated with various delivery agents that aids their entry into the cell. Here, this review article summarizes few of the structural modifications that are performed with PNA, methods used to improve their cellular uptake and shedding light on the applications of PNA in various prospects in biological sciences.

Purpose The development of a new class of engineering materials is the current demand for aircraft and automobile companies. In this context metal, composite materials have a widespread application in different areas of manufacturing sectors. Design/methodology/approach In this paper, an attempt is made to develop the aluminium-based nano metal matrix composite reinforced with graphene nanoparticles (GNP) by using the stir casting method. Different weight percentage (0.4%, 0.8% and 1.2% by weight) of GNPs are used to fabricate metal matrix composites (MMCs). The developed nanocomposites were further validated by density calculation and optical microstructures to discuss the distribution of GNPs. The tensile test was conducted to determine the strength of the developed MMCs and also supported by fractographic analysis. In addition to it, the Rockwell hardness test and impact test (toughness) with fracture analysis were also conducted to strengthen the present work. Findings The results reveal the uniform distribution of GNPs into the matrix material. The yield strength and ultimate tensile strength obtained a maximum value of 155.67 MPa and 170.28 MPa, respectively. The hardness value (HRB) is significantly increased and 84 HRB was obtained for the sample with AA1100/0.4% GNP, while maximum hardness value (94 HRB) was obtained for the sample AA1100/1.2% GNP. The maximum value of toughness 14.3 Jules/cm2 is recorded for base alloy AA1100 while increasing the reinforcement percentage, it decreases up to 9.7 Jules/cm2 for AA1100/1.2% GNP. Originality/value Graphene nanoparticles are used to develop nanocomposites, which is one of the suitable alternatives for heavy engineering materials such as steels and cast irons. It has improved microstructural and mechanical properties which makes it preferable for many engineering and structural applications.

The novel SARS-CoV-2 is the etiological agent causing the Coronavirus disease 2019 (COVID-19), which continues to become an inevitable pandemic outbreak. Over a short span of time, the structures of therapeutic target proteins for SARS-CoV-2 were identified based on the homology modelled structure of similar virus, SARS-CoV that transmitted rapidly in 2003. Since the outset of the disease, the research community has been looking for a potential drug lead. Out of all the known resolved structures related to SARS-CoV-2; 3-chymotrypsin (3 C) like protease (3CLpro) is considered as an attractive anti-viral drug compound on the grounds of its role in viral replication and probable non-interactive competency to bind to any viral host protein. To the best of our knowledge, till date only one compound has been identified and tested in-vitro as a potent inhibitor of 3CLpro protein, addressed as N3 (PubChem Compound CID: 6323191) and is known to bind irreversibly to 3CLpro suppressing its activity. Using computational approach, we intend to identify a probable natural fungal metabolite to interact and inhibit 3CLpro. Here after performing docking and molecular dynamics of various small molecules derived as a secondary metabolite from fungi, we propose Flaviolin as potent inhibitor of 3CLpro of novel Coronavirus SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

Modern globalisation has escalated anthropocentric sources for heavy metal contamination in diverse natural habitats. Pernicious nature of heavy metals poses a major threat to all life forms in the environment. Heavy metals are not degradable like the organic pollutants but could be transformed to be persistent in a less toxic form. Microbes are the cheap tool as they evolve rapidly to combat heavy metal stress by developing various survival strategies, for instance sequestration or active transportation of metal. Their short generation time, large surface area and ease of genetic manipulation makes them ideal candidates to use for the bioremediation process. Many heavy metal resistant microbes such as species of Bacillus, Pseudomonas, Acidothiobacillus, Saccharomyces, Geobacter and Rhizophus have been used for remediation of heavy metal contaminated sites. The effectiveness of bioremediation technique depends upon various factors, including biotic as well as abiotic, which mainly determine bio-availability of metal for remediation. The different metal microbe interactions such as sorption, accumulation, mineralization, transformation and solubilization are responsible for tapering heavy metal concentration at various loci or sites. The review emphasizes on the different interactions of the microbes with heavy metals, their survival strategies and the applications of the resistant strains in remediation.

Quorum sensing in bacteria is a cell density-dependent phenomenon in which, a community of cells communicate with each other using signalling molecules belonging to various families of which N-acyl homoserine lactone (AHL) is one. AHL acts via ligand-receptor interaction where receptors of AHL differ from species to species, and possess great degree of similarity in conformation at the active site. A macromolecule, LasR, is a receptor protein that binds to N-(3-oxododecanoyl)-L-homoserinelactone (OdDHL), a type of AHL, viz. responsible for biofilm formation in Pseudomonas aeruginosa. Similar macromolecule LuxR, like LasR, found in Vibrio sp. identifies a different AHL, N-(3-oxohexanoyl)-L-homoserine lactone (OhHSL), responsible for the phenomenon of bioluminescence. In silico study depicted that curcumin could bind to both LasR and LuxR by unique sets of hydrogen bonding and hydrophobic interactions that can lead to the inactivation of these proteins, enabling this plant-derived organic AHL antagonist to be categorized as a quorum sensing inhibitor (QSI). To prove this hypothesis, curcumin was treated on P. aeruginosa to access the reduction in biofilm formation and on V. alginolyticus to check its efficacy to reduction in bioluminescence by inhibition of QS. The results of these studies proved curcumin to be an efficient QSI.

Plastic comprises of variety of polymers and has many applications, but the waste generated by plastic pose threat to environment and marine life. Plastic can be classified into two types: thermoplastics and thermosetting and are divided into 7 different categories: (Polyethylene Terephthalate [PETE], High-Density Polyethylene [HDPE], Polyvinyl Chloride [PVC], Low-Density Polyethylene [LDPE], Polypropylene [PP], Polystyrene or Styrofoam [PS]Polycarbonate or ABS [others]). To curb the deleterious effects of plastic waste various methods have been devised and utilized that include chemical, physical and biological treatments. One of the aspects primarily focused by the researchers is the phenomenon of biodegradation and there are many microorganisms (bacteria) that have the ability to carry out this particular process. These bacteria assist biodegradation by production of several enzymes like PETases and MHETases. There are few microorganisms that have been listed which cannot be applied for industrial use due to its low biodegradation capacity. To overcome this problem, PHA is one of the alternatives to replace the synthetic plastic due to its high degrading capacity.

There persists a constant threat from multidrug resistance being acquired by all human pathogens that challenges the well-being of humans. This phenomenon is predominantly led by Pseudomonas aeruginosa which is already resistant to the current generations of antibiotic by altering its metabolic pathways to survive. Specifically for this microbe the phenomenon of quorum sensing (QS) plays a crucial role in acquiring virulence and pathogenicity. QS is simply the cross talk between the bacterial community driven by signals that bind to receptors, enabling the entire bacterial microcosm to function as a single unit which has led to control P. aeruginosa cumbersome even in presence of antibiotics. Inhibition of QS can, therefore, be of a significant importance to curb such virulent and pathogenic strains of P. aeruginosa. Natural compounds are well known for their antimicrobial properties, of which, information on their mode of action is scarce. There can be many antimicrobial phytochemicals that act by hindering QS-pathways. The rationale of the current study is to identify such natural compounds that can inhibit QS in P. aeruginosa driven by LasR, PhzR, and RhlR dependent pathways. To achieve this rationale, in silico studies were first performed to identify such natural compounds which were then validated by in vitro experiments. Gingerol and Curcumin were identified as QS-antagonists (QSA) which could further suppress the production of biofilm, EPS, pyocyanin, and rhamnolipid along with improving the susceptibility to antibiotics.

Life expectancy (LE) models have vast effects on the social and financial structures of many countries around the world. Many studies have suggested the essential implications of Life expectancy predictions on social aspects and healthcare system management around the globe. These models provide many ways to improve healthcare and advanced care planning mechanism related to society. However, with time, it was observed that many present determinants were not enough to predict the longevity of the generic set of population. Previous models were based upon mortality-based knowledge of the targeted sampling population. With the advancement in forecasting technologies and rigorous work of the past, individuals have proposed this fact that other than mortality rate, there are still many factors needed to be addressed in order to deduce the standard Predicted Life Expectancy Models (PrLE). Due to this, now Life expectancy is being studied with some additional set of interests into educational, health, economic, and social welfare services. In the Analysis, the authors have implemented different machine learning algorithms and have achieved better accuracy based on pertinent features of the dataset.

The COVID-19 pandemic has adversely affected the lives of millions of people worldwide. With an alarming increase in COVID-19 cases, it is important to detect and diagnose COVID-19 in its early stages to prevent its spread. To diagnose remote patients, the Internet can be useful for accessing data of that patient. But, the Internet has also had issues related to data security, reliability, and privacy. Motivated by these challenges, in this paper, we propose a Blockchain (BC) based COVID-19 detection scheme (BCovX) for fast and reliable diagnosis of COVID-19 using chest X-Ray (CXR) images. For fast and accurate detection of COVID-19 using CXR, BCovX consists of a Convolutional Neural Network (CNN) model, using which a patient can be diagnosed for COVID-19 remotely. CNNs have performed successfully in medical imaging classification. BCovX provides reliable and secure data access and exchange using BC and smart contracts (SC). To solve issues related to data storage and its associated cost, the InterPlanetary File System (IPFS) protocol is used to store medical data. We also present a real-time SC developed in Solidity to govern the transaction between the patient and the doctor. The SC has been compiled and deployed on Remix Integrated Development Environment (IDE). Finally, we have evaluated the performance of BCovX with traditional schemes in terms of storage cost, bandwidth requirements, and accuracy of the CNN model.

With the advent of the Internet, the gaming industry has grown tremendously in business, which also raises concerns for cheating and unfair gameplay. In this paper, we propose a novel approach (GiNA) using Blockchain technology to address a few problems with online Peer-to-Peer (P2P) games. GiNA uses two different data packet transfer schemes to ensure the security and authenticity of the data packet sent and received by game clients. More sensitive data uses a Smart contract-based ON-CHAIN data packet transfer solution and less sensitive data uses an OFF-CHAIN data packet transfer solution with end-to-end encryption for data security. A marketplace where peers can buy and sell purchasable assets with the help of Gicoins. Gicoins is a stable token with compliance with the ERC 20 token of Etheruem Blockchain. Later, a low cost and low bandwidth utilization data storage solution is proposed for storing data in a decentralized and distributed manner. Results show that the performance of the proposed approach GiNA is better in comparison to the traditional approaches with parameters such as latency, scalability, packet loss percentage, Blockchain (BC) performance, and data storage comparison.

Financial institutions have made lives easier for a lot of individuals and organizations that would earlier use to face capital shortage now and then. Therefore, it becomes necessary to make the financial systems more reliable, secure, time-conserving, and cost-effective. Although several approaches have already been proposed, all of these tend to fail on at least one of the key features, i.e., trust. Motivated by this, in this paper, we propose DeLend, an Ethereum blockchain-based peer-to-peer (P2P) lending system. In DeLend, the problems of security, trust, and reliability have been solved with the help of Ethereum-based smart contracts (SCs). To make the system middlemen-free and much more cost-effective, we use the interplanetary file system (IPFS) protocol as a data storage. Through extensive simulation, we show that DeLend requires less bandwidth, which makes it a suitable enabling technology for the next generation of cellular networks, i.e. 6G. Finally, DeLend’s performance evaluation demonstrates its efficacy compared to traditional lending schemes.

The rapid growth and advancement of technology in industries provide a better quality of services to the end-user in the industrial Internet of Things (IIoT). The digital twin (DT) is an innovative technology recently developed in Industry 4.0 to provide a virtual representation of physical components, products, or equipment such as computer numerical control (CNC) machines. It can be used to run simulations before manufacturing. However, traditional DT platforms lack data privacy, traceability, immutability, authentication of stakeholders. Moreover, manual prediction of the wearing of the tool condition of the CNC machine is challenging. Motivated from these gaps, in this paper, we propose a six-layered architecture for DT of CNC, which predicts CNC tool wear detection using a novel ensemble technique based soft voted prediction model consisting of XGBoost, random forest, and AdaBoost models. The proposed architecture also incorporates the public Ethereum blockchain (BC) to maintain the aforementioned issues of authentication, traceability, and transparency through constraints and automation programmed into the smart contracts (SC) developed. We evaluate the proposed scheme’s performance through simulation and compare it with other traditional approaches concerning several performance parameters (accuracy, F1-score, precision, and recall). The result shows that the proposed approach outperforms the traditional approaches on these same performance parameters such as accuracy, F1-score, precision, and recall.

Generally, to make a campaign,startup, or any innovative idea successful requires some amount of donation. Fundraising or let us say Crowdfunding is an efficient way to raise money for your ideas, campaigns, startups etc. There are a lot of platforms available online and they provide space for setting up your own campaign so that you can gets funds for your campaign. people can go and contribute to any idea they like and get benefit from the pledge that you make. Certainly, there are lot of drawbacks to this model. There is no transparency and no assurance that your money is being put to the right use, there are charges to use the platform and many other issues. We try to over come these issues by making a fundraising platform using smart contract in solidity. This will be more secure as it uses Ethereum blockchain to make all the transactions and all the transactions are ethereum based. Not only this but the contributors have the right to vote for a transaction and only when a minimum consensus is achieved the requested transaction can be made.Contributors can have their own pool of contributors which can be achieved by multi-signature wallet.By creating a multisigned wallet , there will be two factor authentication mechanism to access funds, which are related more to security concerns. This not only enables a transparent transaction but also develops trust in the users of the platform. This not only resolves major drawbacks faced in the current live non blockchain based platforms like Kickstarter but also brings in more efficient platform to serve the purpose.”

Microorganisms can utilize an extensive assortment of carbon and nitrogen sources as well as various added nutrients ranging from simple to complex. Depending on the microbe and the metabolic pathway they undergo, these nutrients are efficiently converted into complex and diverse biopolymers with varied physico-chemical properties. Exopolysaccharides (EPS) are biopolymers that primarily contain- carbohydrates. The extensively studied EPS producing bacteria include Leuconostoc mesenteroides, Xanthomonas campestris, Acinetobacter calcoaceticus, Lactobacillus sp. and Alkaligenes sp. However, some prominent fungal exopolysaccharides produced by Aspergillus niger, Lentinula edodes, Fusarium solani, Botryosphaeria rhodina, Coriolus versicolor have also been put to commercial use. While the microbes may vary substantially in their physiology, the production of EPS depends largely on the optimization of the growth by varying various parameters influencing growth and the meticulous designing of its production media. EPS acts as an invaluable asset for the producing microbe by providing manifold benefits including but not restricted to: protection against- desiccation, starvation, phagocytosis, UV radiation, environmental stress and water retention. Being eco-friendly and biodegradable, major microbial EPS such as; dextran, xanthan, alginate, hyaluronan, pullulan, chitosan and lentinam have found numerous vital applications in pharmaceutical, agriculture, food and cosmetics industries. This review provides an inclusive insight into the world of microbial exopolysaccharides covering its major aspects, namely- its types, biosynthesis and the factors that influence its production along with various techniques used for its recovery and further characterization. Special emphasis is placed on the applications of EPS in various large-scale commercial and industrial sectors.

Radionuclides are present in minute concentrations in soils, especially around atomic power stations. Several microorganisms have been reported to grow in presence of radionuclides and even extreme gamma-radiation. Deinococcus radiodurans serves as the model radioresistant bacterium owing to its tolerance to extreme levels of gamma-radiation. In the present study, the soil sample was randomly collected from the area around Kakrapar Atomic Power Station, Surat (India) and was characterized physico-chemically. Based on the inductively coupled plasma-optical emission spectrometry (ICP-OES) analysis, the soil was found to be rich in iron, titanium and magnesium. The nutrient medium was used for the cultivation and isolation of indigenous bacterial flora which were then characterized for their biochemical and metabolic potential. Twenty-five isolates were isolated which were sequentially screened to five. Furthermore, the five screened-in isolates exhibited the ability to produce exopolysaccharide (EPS) and biofilm, serving as one of the criteria for secondary screening of two isolates. The two screened bacteria were then identified as Providencia vermicola AM3 and Ochrobactrum sp. AM7 by 16S partial rRNA sequencing and their nucleotide sequences have been submitted to GenBank (NCBI). Additional optimization of medium components supporting the growth as well as facilitating the production of EPS by isolates P. vermicola AM3 and Ochrobactrum sp. AM7 is required for their potential application in bioremediation of radionuclide containing waste.

Graphic abstract The latest global outbreak of 2019 respiratory coronavirus disease (COVID-19) is triggered by the inception of novel coronavirus SARS-CoV2. If recent events are of any indicators of the epidemics of past, it is undeniable to state a fact that the SARS-CoV2 viral infection is highly transmissible with respect to its previously related SARS-CoV’s. Papain-like protease (PLpro) is an enzyme that is required by the virus itself for replicating into the host system; and it does so by processing its polyproteins into a functional replicase complex. PLpro is also known for downregulating the genes responsible for producing interferons, an essential family of molecules produced in response to viral infection, thus making this protein an indispensable drug target. In this study, PLpro inhibitors were identified through high throughput structure-based virtual screening approach from NPASS natural product library possessing ~ 35,000 compounds. Top five hits were scrutinised based on structural aromaticity and ability to interact with a key active site residue of PLpro, Tyr268. For second level of screening, the MM-GBSA End-Point Binding Free Energy Calculation of the docked complexes was performed, which identified Caesalpiniaphenol A as the best hit. Caesalpiniaphenol A not only possess a double ring aromatic moiety but also has lowest minimum binding energy, which is at par with the control GRL0617, the only known inhibitor of SARS-CoV2 PLpro. Details of the Molecular Dynamics (MD) simulation and ADMET analysis helped to conclusively determine Caesalpiniaphenol A as potentially an inhibitor of SARS-CoV2 PLpro.

The flexibility of microbes to undergo or adapt to the changes in their physiology and genotypical traits has enabled the microbes acquiring resistance to latest or recently discovered drugs which have consequently led to the menace of multidrug resistance (MDR). There is a surge in the discovery of novel antibiotics to counter the rising MDR phenomena, and in such a quest, for investigating an efficient alternative mechanism or compound to combat MDR, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) has piqued the interests of the researchers across the globe. CRISPR-Cas9 technology is a genome-editing tool with successful widespread applications in cell lines, plants, animals, and even in human clinical trials, and it is seriously being considered as a potential candidate for countering MDR. This review encompasses the broad scope of CRISPR-Cas9 along with its various variations, underlying principles, mechanisms, as well as applications. Furthermore, the implications of recent advancements in various disciplines are highlighted to enhance the applicability of this technique. Consequently, its research gaps and challenges are also identified so that they can be addressed in the possible future thereby further expanding the lore of CRISPR-Cas9 technique.

The textile industry is a complex commercial avenue which deals with multiple processes that can lead to significant pollution. Pretreatment of textile, coloring, and decolorization requires complex chemical processes that develop noxious compounds which cause pollution in the environment. For instance, several alkali and acids are used during the pretreatment of textile products which are not environment-friendly. To overcome such limitations, scientists across the globe have made a progress by making use of microorganisms at various stages in the textile industry to curb the production of contaminants. There are varieties of microbes that possess a plethora of abilities to thrive in different environments which have enabled then to produce a variety of enzymes. Of the gazillions enzymes known to be produced by microbes, amylase, protease, lipase, pectinase, xylanase, ligninase, and cellulase are most been exploited in the textile industry for the pretreatment of textile. These enzymes can substitute several hazardous chemicals used for the same processes. Microbes are also known to produce a variety of pigments which have shown the potentials to replace persistent azo dyes. Of all the most important applications of microbes in textile industries, microbes have found significant applications in the effluent treatment process that make use of its wide and varied abilities to encounter with harmful compounds. The microbes have also shown to degrade azo dyes, making them degradable, bringing down their BOD and COD levels, remediating heavy metals from the effluents, and making these microbially treated effluents to be safe for environmental disposal, without disturbing the ecosystem. Microbially mediated processes at various stages in the textile industry best complement the green chemistry.

Microorganisms are well capable of removing heavy metals by different mechanisms especially where the process of biosorption has attracted researchers in the recent years. Various bacteria and fungi are currently being used for biosorption of heavy metals, however, reports suggesting the use of bioluminescent Vibrio sp. for metal biosorption are rare. In this study, the dead biomass of Vibrio alginolyticus PBR1 was employed to remove two metals, cadmium (Cd) and lead (Pb) from a single aqueous system. The Box-Behnken design (BBD), a Response Surface Method (RSM), was used to optimize biosorption of metals by V. alginolyticus PBR1. The three major factors; pH, biosorbent dosage and metal concentration were optimized to remove the metals efficiently. The optimum conditions for V. alginolyticus PBR1 were pH 5.7, biosorbent dosage of 2.0 g L−1 and metal concentration of 50 mg L−1 for each metal showed to have removal efficiencies of 59.78 % and 82.20 % for Cd and Pb, respectively. Furthermore, the possible interactions between functional groups present on cell surface and metals were studied using Fourier Transform Infrared (FTIR) spectroscopy. The study provides potential application of bioluminescent Vibrio sp. for removing two metals simultaneously from heavy metal contaminated aqueous solution.