Microbial strategies for copper pollution remediation: Mechanistic insights and recent advances.

Environmental contamination is aninsistent concern affecting human health and the ecosystem. Wastewater, containing heavy metals from industrial activities, significantly contributes to escalating water pollution. These metals can bioaccumulate in food chains, posing health risks even at low concentrations. Copper (Cu), an essential micronutrient, becomes toxic at high levels. Activities like mining and fungicide use have led to Copper contamination in soil, water, and sediment beyond safe levels. Copper widely used in industries, demands restraint of heavy metal ion release into wastewater for ecosystem ultrafiltration, membrane filtration, nanofiltration, and reverse osmosis, combat heavy metal pollution, with emphasis on copper.Physical and chemical approaches are efficient, large-scale feasibility may have drawbackssuch as they are costly, result in the production of sludge. In contrast, bioremediation, microbial intervention offers eco-friendly solutions for copper-contaminated soil. Bacteria and fungi facilitate these bioremediation avenues as cost-effective alternatives. This review article emphasizes on physical, chemical, and biological methods for removal of copper from the wastewater as well asdetailing microorganism's mechanisms to mobilize or immobilize copper in wastewater and soil.

Spatio-temporal variability of public water supply characteristics and associated health hazards for children and adults in selected locations of Ambala, India.

The contamination of public water supply and groundwater resources is a major concern in many parts of developing nations. Polluted water poses serious health risks to humans and the environment. This research was conducted to investigate the seasonal variations of the water quality parameters in the public water supply. To assess the supply water quality in different blocks of Ambala District, hydro-chemical analysis was conducted after a series of systematic sampling in various locations. The statistical tools for water quality indexing including water quality indexing (WQI), heavy metal pollution indexing (HMPI), pollution indexing (PI), overall pollution indexing (OPI), metal indexing (MI), and hazard indexing (HI) were used for data as well as the health hazard analysis through water pathway. Overall, 40 water samples were taken from the public water supply systems covering winter and summer seasons, and the levels of pH, total dissolved solids (TDS), EC, F- , Cl- , NO3 - , SO4 2- , HCO3 - , As, B, Cd, Co, Pb, Zn, Cr, Fe, and Mn were investigated. The weight arithmetic index method was used for WQI, and water pollution indices such as HMPI, PI, OPI, and MI were calculated using different models to check the severity of contamination. The mean hazard quotient and hazard index values calculated using the concentration levels of As, B, Cd, Co, Pb, Cr, Fe, Mn, Zn, F- , and NO3 - reveal that supply water may pose a significant health risk to both adults and children that further varies with temporal and spatial changes. During both seasons, a high carcinogenic risk for both adults and children was observed in the studied area because of high levels of As, Pb, Cd, and NO3 - . PRACTITIONER POINTS: The quality of public supply water was assessed at the selected sites of Ambala, India. High levels of NO3 - , As, Cd, and Pb were observed posing a health risk to adults and children via water pathway. 95% of the samples qualified for the excellent water quality category with respect to the levels of F- , Cl- , NO3 - , SO4 2- , HCO3 - , pH, EC, and TDS. Statistical analysis (HMPI, PI, MI, OPI, HI) using different models revealed water contamination with reference to the levels of NO3 - , As, Pb, Cr, Ni, and Cd. Immediate measures are needed to uphold the safety and health of the natives.

Construction of a genetic linkage map and QTL mapping of fruit quality traits in guava (Psidium guajava L.).

Guava (Psidium guajava L.) is an important fruit crop of the Indian sub-continent, with potential for improvements in quality and yield. The goal of the present study was to construct a genetic linkage map in an intraspecific cross between the elite cultivar 'Allahabad Safeda' and the Purple Guava landrace to identify the genomic regions responsible for important fruit quality traits, viz., total soluble solids, titratable acidity, vitamin C, and sugars. This population was phenotyped in field trials (as a winter crop) for three consecutive years, and showed moderate-to-high values of heterogeneity coefficients along with higher heritability (60.0%-97.0%) and genetic-advance-over-mean values (13.23%-31.17%), suggesting minimal environmental influence on the expression of fruit-quality traits and indicating that these traits can be improved by phenotypic selection methods. Significant correlations and strong associations were also detected among fruit physico-chemical traits in segregating progeny. The constructed linkage map consisted of 195 markers distributed across 11 chromosomes, spanning a length of 1,604.47 cM (average inter-loci distance of 8.80 markers) and with 88.00% coverage of the guava genome. Fifty-eight quantitative trait loci (QTLs) were detected in three environments with best linear unbiased prediction (BLUP) values using the composite interval mapping algorithm of the BIP (biparental populations) module. The QTLs were distributed on seven different chromosomes, explaining 10.95%-17.77% of phenotypic variance, with the highest LOD score being 5.96 for qTSS.AS.pau-6.2. Thirteen QTLs detected across multiple environments with BLUPs indicate stability and utility in a future breeding program for guava. Furthermore, seven QTL clusters with stable or common individual QTLs affecting two or more different traits were located on six linkage groups (LGs), explaining the correlation among fruit-quality traits. Thus, the multiple environmental evaluations conducted here have increased our understanding of the molecular basis of phenotypic variation, providing the basis for future high-resolution fine-mapping and paving the way for marker-assisted breeding of fruit-quality traits.

Construction of Genetic Linkage Map and Mapping QTL Specific to Leaf Anthocyanin Colouration in Mapping Population 'Allahabad Safeda' × 'Purple Guava (Local)' of Guava (Psidium guajava L.).

In the present investigation, F1 hybrids were developed in guava (Psidium guajava L.) by crossing high leaf-anthocyanin reflective-index (ARI1) content cultivars purple guava (local) 'PG', 'CISH G-1' and low leaf-ARI1 content cultivar Seedless 'SL' with Allahabad Safeda 'AS'. On the basis of phenotypic observations, high ARI1 content was observed in the cross 'AS' × 'PG' (0.214). Further, an SSR-markers-based genetic linkage map was developed from a mapping population of 238 F1 individuals derived from cross 'AS' × 'PG'. The linkage map comprised 11 linkage groups (LGs), spanning 1601.7 cM with an average marker interval distance of 29.61 cM between adjacent markers. Five anthocyanin-content related gene-specific markers from apple were tested for parental polymorphism in the genotypes 'AS' and 'PG'. Subsequently, a marker, viz., 'MdMYB10F1', revealed a strong association with leaf anthocyanin content in the guava mapping population. QTL (qARI-6-1) on LG6 explains much of the variation (PVE = 11.51% with LOD = 4.67) in levels of leaf anthocyanin colouration. This is the first report of amplification/utilization of apple anthocyanin-related genes in guava. The genotypic data generated from the genetic map can be further exploited in future for the enrichment of linkage maps and for identification of complex quantitative trait loci (QTLs) governing economically important fruit quality traits in guava.

Development of Genome-Wide Functional Markers Using Draft Genome Assembly of Guava (Psidium guajava L.) cv. Allahabad Safeda to Expedite Molecular Breeding.

Guava (Psidium guajava L.), a rich source of nutrients, is an important tropical and subtropical fruit of the Myrtaceae family and exhibits magnificent diversity. Genetic diversity analysis is the first step toward the identification of parents for hybridization, genetic mapping, and molecular breeding in any crop species. A diversity analysis based on whole-genome functional markers increases the chances of identifying genetic associations with agronomically important traits. Therefore, here, we sequenced the genome of guava cv. Allahabad Safeda on an Illumina platform and generated a draft assembly of ~304 MB. The assembly of the Allahabad Safeda genome constituted >37.95% repeat sequences, gene prediction with RNA-seq data as evidence identified 14,115 genes, and BLAST n/r, Interproscan, PfamScan, BLAST2GO, and KEGG annotated 13,957 genes. A comparative protein transcript analysis of tree species revealed the close relatedness of guava with Eucalyptus. Comparative transcriptomics-based SSR/InDel/SNP-PCR ready genome-wide markers in greenish-yellow skinned and white fleshed-Allahabad Safeda to four contrasting cultivars viz apple-color-skinned and white-fleshed-Lalima, greenish-yellow-skinned and pink-fleshed-Punjab Pink, purple-black-skinned and purple-fleshed-Purple Local and widely used rootstock-Lucknow-49 were developed. The molecular markers developed here revealed a high level of individual heterozygosity within genotypes in 22 phenotypically diverse guava cultivars. Principal coordinate, STRUCTURE clustering, and neighbor-joining-based genetic diversity analysis identified distinct clusters associated with fruit skin and flesh color. The genome sequencing of guava, functional annotation, comparative transcriptomics-based genome-wide markers, and genetic diversity analysis will expand the knowledge of genomes of climacteric fruits, facilitating trait-based molecular breeding and diversifying the nutritional basket.

Deciphering pollution vulnerability zones of River Yamuna in relation to existing land use land cover in Panipat, Haryana, India.

Rivers are one of the major freshwater resources, which provide water for irrigation, domestic, recreational, environmental, and industrial purposes, but they are extremely vulnerable to pollution due to discharge of untreated waste. Establishing the baseline river water quality data is important, so that monitoring changes over time, assessing impacts of particular developmental projects and setting water quality standards for the protection of the river, can be undertaken. In the present study, water quality assessment was done for a segment of Yamuna River passing through Panipat district, Haryana, India. This study is an attempt to know the impact of wastewater generated due to urban and industrial activities taking place in Panipat city and nearby areas, on River Yamuna. Furthermore, vulnerability zone of River Yamuna was delineated using CCME-WQI, NSF-WQI, and hierarchical cluster analysis (HCA). The water quality samples were further evaluated for the agricultural and industrial purposes to determine whether the water can be used for irrigation and industrial requirements. The study also considered the existing land use land cover (LULC) on left and right banks of the River Yamuna and the wastewater carrying drain. River Yamuna travels nearly a distance of ≈ 44 Kms in and around Panipat district and the results of the study indicated that nearly 13 Km stretch of River is more vulnerable to pollution. Thus, it is suggested that wastewater discharge regulation, installation of effluent treatments plants, and maintenance of environmental flow are prerequisite to protect and restore the River Yamuna.

RNA-sequencing based gene expression landscape of guava cv. Allahabad Safeda and comparative analysis to colored cultivars.

BACKGROUND: Guava (Psidium guajava L.) is an important fruit crop of tropical and subtropical areas of the world. Genomics resources in guava are scanty. RNA-Seq based tissue specific expressed genomic information, de novo transcriptome assembly, functional annotation and differential expression among contrasting genotypes has a potential to set the stage for the functional genomics for traits of commerce like colored flesh and apple color peel. RESULTS: Development of fruit from flower involves orchestration of myriad molecular switches. We did comparative transcriptome sequencing on leaf, flower and fruit tissues of cv. Allahabad Safeda to understand important genes and pathways controlling fruit development. Tissue specific RNA sequencing and de novo transcriptome assembly using Trinity pipeline provided us the first reference transcriptome for guava consisting of 84,206 genes comprising 279,792 total transcripts with a N50 of 3603 bp. Blast2GO assigned annotation to 116,629 transcripts and PFam based HMM profile annotated 140,061 transcripts with protein domains. Differential expression with EdgeR identified 3033 genes in Allahabad Safeda tissues. Mapping the differentially expressed transcripts over molecular pathways indicate significant Ethylene and Abscisic acid hormonal changes and secondary metabolites, carbohydrate metabolism and fruit softening related gene transcripts during fruit development, maturation and ripening. Differential expression analysis among colored tissue comparisons in 3 cultivars Allahabad Safeda, Punjab Pink and Apple Color identified 68 candidate genes that might be controlling color development in guava fruit. Comparisons of red vs green peel in Apple Color, white pulp vs red pulp in Punjab Pink and fruit maturation vs ripening in non-colored Allahabad Safeda indicates up-regulation of ethylene biosynthesis accompanied to secondary metabolism like phenylpropanoid and monolignol pathways. CONCLUSIONS: Benchmarking Universal Single-Copy Orthologs analysis of de novo transcriptome of guava with eudicots identified 93.7% complete BUSCO genes. In silico differential gene expression among tissue types of Allahabad Safeda and validation of candidate genes with qRT-PCR in contrasting color genotypes promises the utility of this first guava transcriptome for its potential of tapping the genetic elements from germplasm collections for enhancing fruit traits.