TopHap: rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity.

MOTIVATION: Building reliable phylogenies from very large collections of sequences with a limited number of phylogenetically informative sites is challenging because sequencing errors and recurrent/backward mutations interfere with the phylogenetic signal, confounding true evolutionary relationships. Massive global efforts of sequencing genomes and reconstructing the phylogeny of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains exemplify these difficulties since there are only hundreds of phylogenetically informative sites but millions of genomes. For such datasets, we set out to develop a method for building the phylogenetic tree of genomic haplotypes consisting of positions harboring common variants to improve the signal-to-noise ratio for more accurate and fast phylogenetic inference of resolvable phylogenetic features. RESULTS: We present the TopHap approach that determines spatiotemporally common haplotypes of common variants and builds their phylogeny at a fraction of the computational time of traditional methods. We develop a bootstrap strategy that resamples genomes spatiotemporally to assess topological robustness. The application of TopHap to build a phylogeny of 68 057 SARS-CoV-2 genomes (68KG) from the first year of the pandemic produced an evolutionary tree of major SARS-CoV-2 haplotypes. This phylogeny is concordant with the mutation tree inferred using the co-occurrence pattern of mutations and recovers key phylogenetic relationships from more traditional analyses. We also evaluated alternative roots of the SARS-CoV-2 phylogeny and found that the earliest sampled genomes in 2019 likely evolved by four mutations of the most recent common ancestor of all SARS-CoV-2 genomes. An application of TopHap to more than 1 million SARS-CoV-2 genomes reconstructed the most comprehensive evolutionary relationships of major variants, which confirmed the 68KG phylogeny and provided evolutionary origins of major and recent variants of concern. AVAILABILITY AND IMPLEMENTATION: TopHap is available at https://github.com/SayakaMiura/TopHap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chemical-biological hybrid systems for the metal recovery from waste lithium ion battery.

The metals in the waste lithium-ion battery (LIB) are in complex form with coating materials. It consists of copper and aluminium as coiling metals for anode and cathode covered by black powder containing lithium and cobalt. Chemical-biological hybrid systems are found to be useful for the process of metal extraction from LIB waste compared with the individual technique. Lysinibacillus - citric acid hybrid combination provides a noble pathway for the recovery of lithium and cobalt in one pot process. Citric acid (CA) treatment is used to separates copper and aluminum foil from black powder. It leaves lithium and cobalt in the resultant extractant and by the proposed hybrid combination lithium is further separate through leaching and cobalt through biosorbtion. The hrbrid treatment increases lithium leaching by 25% and cobalt biosorption by 98%.

Improving cellular phylogenies through the integrated use of mutation order and optimality principles.

The study of tumor evolution is being revolutionalized by single-cell sequencing technologies that survey the somatic variation of cancer cells. In these endeavors, reliable inference of the evolutionary relationship of single cells is a key step. However, single-cell sequences contain many errors and missing bases, which necessitate advancing standard molecular phylogenetics approaches for applications in analyzing these datasets. We have developed a computational approach that integratively applies standard phylogenetic optimality principles and patterns of co-occurrence of sequence variations to produce more expansive and accurate cellular phylogenies from single-cell sequence datasets. We found the new approach to also perform well for CRISPR/Cas9 genome editing datasets, suggesting that it can be useful for various applications. We apply the new approach to some empirical datasets to showcase its use for reconstructing recurrent mutations and mutational reversals as well as for phylodynamics analysis to infer metastatic cell migrations between tumors.

TopHap: Rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity.

MOTIVATION: Building reliable phylogenies from very large collections of sequences with a limited number of phylogenetically informative sites is challenging because sequencing errors and recurrent/backward mutations interfere with the phylogenetic signal, confounding true evolutionary relationships. Massive global efforts of sequencing genomes and reconstructing the phylogeny of SARS-CoV-2 strains exemplify these difficulties since there are only hundreds of phylogenetically informative sites and millions of genomes. For such datasets, we set out to develop a method for building the phylogenetic tree of genomic haplotypes consisting of positions harboring common variants to improve the signal-to-noise ratio for more accurate phylogenetic inference of resolvable phylogenetic features. RESULTS: We present the TopHap approach that determines spatiotemporally common haplotypes of common variants and builds their phylogeny at a fraction of the computational time of traditional methods. To assess topological robustness, we develop a bootstrap resampling strategy that resamples genomes spatiotemporally. The application of TopHap to build a phylogeny of 68,057 genomes (68KG) produced an evolutionary tree of major SARS-CoV-2 haplotypes. This phylogeny is concordant with the mutation tree inferred using the co-occurrence pattern of mutations and recovers key phylogenetic relationships from more traditional analyses. We also evaluated alternative roots of the SARS-CoV-2 phylogeny and found that the earliest sampled genomes in 2019 likely evolved by four mutations of the most recent common ancestor of all SARS-CoV-2 genomes. An application of TopHap to more than 1 million genomes reconstructed the most comprehensive evolutionary relationships of major variants, which confirmed the 68KG phylogeny and provided evolutionary origins of major variants of concern. AVAILABILITY: TopHap is available on the web at https://github.com/SayakaMiura/TopHap . CONTACT: s.kumar@temple.edu.

Green and facile method for the recovery of spent Lithium Nickel Manganese Cobalt Oxide (NMC) based Lithium ion batteries.

The research reports a novel green method to use citrus fruits for the management of spent NMC based lithium ion batteries (LIBs). Citrus fruit juice (CJ) can provide an excellent chemical combination to remove the binder and support the leaching with efficiency in between 94% to 100%. CJ have many advantages in LIBs recycling as an economic and green method due to rich in many organic acids like citric and malic acid as complexing agents with ascorbic acid and citrus flavonoids, for the reduction of many heavy metals. Application of CJ can avoid the use of N-Methylpyrrolidine, γ-Butyrolactone, dimethylformamide, and dimethyl sulfoxide like toxic solvents commonly used for peeling off Al/Cu. Furthermore, counterions (like Na+, Mg+, Ca2+) present in CJ was responsible for the improvement in the leaching efficiency of organic acids. A mechanistic pattern of the overall reaction was also proposed and duly supported by various spectroscopic techniques. Binder removal experiment was supported by analytical techniques like XRD, XRF, IR, and FE-SEM, while the metal concentration was monitored by using ICP-MS analysis.