Biology subjects

Gupta, R.

Publications and source records attributed to Gupta, R..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Terpenoid balance in Aspergillus nidulans unveiled by heterologous squalene synthase expression

Filamentous fungi produce numerous uncharacterized natural products (NPs) that are often challenging to characterize due to cryptic expression in laboratory conditions. Previously, we have successfully isolated novel NPs by expressing fungal artificial chromosomes (FACs) from a variety of fungal species into Aspergillus nidulans. Here, we demonstrate a new twist to FAC utility wherein heterologous expression of a Pseudogymnoascus destructans FAC in A. nidulans altered endogenous terpene biosynthetic pathways. In contrast to wildtype, the FAC transformant produced increased levels of squalene and aspernidine type compounds, including three new nidulenes (1-2, 5), and lost nearly all ability to synthesize the major A. nidulans characteristic terpene, austinol. Deletion of a squalene synthase gene in the FAC restored wildtype chemical profiles. The altered squalene to farnesyl pyrophosphate ratio leading to synthesis of nidulenes and aspernidines at the expense of farnesyl pyrophosphate derived austinols provides unexpected insight into routes of terpene synthesis in fungi. TeaserReshaping terpenes: Heterologous FAC expression reroutes terpene pathways.

microbiology↗

bioRxiv2023

A mechanistic study on the tolerance of PAM distal end mismatch by SpCas9

CRISPR-Cas9 is the newest technology available for targeted genome editing. It is very efficient and cheap compared to other genome editing techniques. However, its therapeutic application is limited due to its off-target activity. To have a better understanding of this off-target effect, we concentrated our efforts on its mismatch-prone PAM distal end. Current off-target prediction algorithms use RNA-DNA complementation derived energy as a major factor in predicting off-target effect. RNA-DNA complementation derived energy drives Cas9 conformational change, which in turn drives its functional activity. In the case of lower RNA-DNA complementarity, a partial conformational change occurs resulting in a slower reaction rate and partial activity. However, extensive mismatches are often tolerated despite lower complementation derived energy available from RNA: DNA duplex formation. Thus, the off-target activity of Cas9 depends directly on the nature of mismatches which in turn result in deviation of the active site of the enzyme due to structural instability in the duplex strand. In order to test the hypothesis, we have designed an array of mismatched target sites and performed in vitro and cell line-based experiments to assess the effects of PAM distal mismatches in Cas9 activity. For further mechanistic validation, Molecular dynamics simulation was performed and it revealed that certain mismatch mutations induced pronounced conformational instability within the RNA-DNA duplex, leading to elevated root mean square deviation (RMSD) values. We found that, target sites having mismatches in the 18th to 16th position upstream of the PAM showed no to little activity.

genomics↗

bioRxiv2023

De novo drug designing coupled with brute force screening and structure guided lead optimization gives highly specific inhibitor of METTL3: a potential cure for Acute Myeloid Leukaemia

Expression of METTL3, a SAM dependent methyltransferase, which deposits m6A on mRNA is linked to poor prognosis in Acute Myeloid Leukaemia and other type of cancers. Down regulation of this epitranscriptomic regulator has been found to inhibit cancer progression. Silencing the methyltransferase activity of METTL3 is a lucrative strategy to design anticancer drugs. In this study 3600 commercially available molecules were screened against METTL3 using brute force screening approach. However, none of these compounds take advantage of the unique Y-shaped binding cavity of the protein, raising the need for de novo drug designing strategies. As such, 125 branched, Y-shaped molecules were designed by "stitching" together the chemical fragments of the best inhibitors that interact strongly with the METTL3 binding pocket. This results in molecules that have the three-dimensional structure and functional groups which enable it to fit in the METTL3 cavity like fingers in a glove, having unprecedented selectivity and binding affinities. The designed compounds were further refined based on Lipinskis rule, docking score and synthetic accessibility. The molecules faring well in these criteria were simulated for 100ns to check the stability of the protein inhibitor complex followed by binding free energy calculation.

bioinformatics↗

bioRxiv2023

A novel glideosome-associated protein S14 coordinates sporozoite gliding motility and infectivity in mosquito and mammalian hosts

Plasmodium sporozoites are the infective forms of the malaria parasite in the vertebrate host. Gliding motility allows sporozoites to migrate and invade the salivary gland and hepatocytes. Invasion is powered by an actin-myosin motor complex linked to glideosome. However, the gliding complex and the role of several glideosome-associated proteins (GAPs) are poorly understood. In silico analysis of a novel protein, S14, which is uniquely upregulated in salivary gland sporozoites, suggested its association with glideosome-associated proteins. We confirmed S14 expression in sporozoites using real-time PCR. Further, the S14 gene was endogenously tagged with 3XHA-mCherry to study expression and localization. We found its expression and localization on the inner membrane of sporozoites. By targeted gene deletion, we demonstrate that S14 is essential for sporozoite gliding motility, salivary gland, and hepatocyte invasion. The gliding and invasion-deficient S14 KO sporozoites showed normal expression and organization of IMC and surface proteins. Using in silico and the yeast two-hybrid system, we showed the interaction of S14 with the glideosome-associated proteins GAP45 and MTIP. Together, our data show that S14 is a glideosome-associated protein and plays an essential role in sporozoite gliding motility, which is critical for the invasion of the salivary gland, hepatocyte, and malaria transmission.

microbiology↗

bioRxiv2023

Factorial state-space modelling for kinetic clustering and lineage inference

Single-cell RNA sequencing (scRNAseq) protocols measure the abundance of expressed transcripts for single cells. Gene expression profiles of cells (cell-states) represent the functional properties of the cell and are used to cluster cell-states that have a common functional identity (cell-type). Standard clustering methods for scRNAseq data perform hard clustering based on KNN graphs. This approach implicitly assumes that variation among cell-states within a cluster does not correspond to changes in functional properties. Differentiation is a directed process of transitions between cell-types via gradual changes in cell-states over the course of the process. We propose a latent state-space Markov model that utilises cell-state transitions derived from RNA velocity to model differentiation as a sequence of latent state transitions and to perform soft kinetic clustering of cell-states that accommodates the transitional nature of cells in a differentiation process. We applied this model to the differentiation of Radial-glia cells into mature neurons and demonstrate the utility of our method in discriminating between functional and transitional cell-states.

bioinformatics↗

bioRxiv2023

A demand-based framework explains prioritization strategies upon transient limitations of different amino acids.

Cells require disparate amounts of distinct amino acids, which themselves have discrete biosynthetic costs. However, it remains unclear if and how cells respond differently to their scarcity. To explore this, we re-organized amino acids into distinct groups based on their metabolic origins. Subsequently, using yeast we assessed responses to transient disruptions in amino acid supply, and uncover diverse restoration responses for distinct amino acids. Cells hierarchically prioritize restoring glutamate-, sulfur-, pentose-phosphate- and pyruvate-derived amino acids. Particularly, the strongest response is to the glutamate-derived amino acid arginine. We find that the extent and priority of the restoration response is determined by the composite demand for an amino acid, coupled with low individual biosynthetic costs of that amino acid. We propose that cells employ a conserved strategy guided by the law of demand, to prioritize amino acids restoration upon transient limitation.

systems biology↗

bioRxiv2023

The Endosomal pH Regulator NHE6 is Required for Insulin-Stimulated Glucose Uptake in Adipocytes

ObjectiveTrafficking of GLUcose Transporter isoform 4 (GLUT4) from the adipocyte vesicular pool to the cell surface is tightly regulated by insulin to maintain glucose homeostasis in response to changing demands in energy consumption. Previously, endosomal Na+/H+ exchanger 6 (NHE6, gene name SLC9A6) was identified in adipocyte plasma membranes and shown to associate with GLUT4-positive vesicles. However, the functional contribution of NHE6 to GLUT4 trafficking and glucose uptake remained uncharacterized. MethodsNHE6 was knocked down in 3T3L1 cells either before or after differentiation into adipocytes using lentiviral delivery of shRNA. Uptake of [3H] 2-deoxyglucose into adipocytes was quantified in response to insulin. We used epitope tagged constructs to distinguish between localization of vesicular and surface levels of NHE6 and GLUT4 proteins. Protein and transcript levels of components of the glucose signaling pathway were monitored by qPCR and Western analysis, respectively, in response to NHE6 knockdown and/or treatment with chemical modulators of endosomal pH. ResultsWe show that insulin-stimulated glucose uptake in adipocytes is severely impaired upon NHE6 depletion. Correspondingly, insulin-stimulated surface expression of GLUT4 at the adipocyte plasma membrane was diminished in NHE6 knockdown cells due to a post-transcriptional decrease in basal GLUT4. Metformin response of GLUT4 was also muted in the absence of NHE6. Further, we demonstrate diminished activation of the GLUT4 translocation pathway in the absence of NHE6 via reduced expression of the insulin receptor and reduced phosphorylation of the downstream effector kinase Akt. Components of GLUT4 storage vesicles, including GLUT4, LRP1 and sortilin were downregulated in NHE6-knockdown adipocytes under basal conditions. Proteostatic control of key components of the insulin signaling pathway (insulin receptor, GLUT4) could be restored by chemical bypass of NHE6 using the V-ATPase inhibitor bafilomycin or the Na+/H+ exchanger mimetic monensin. ConclusionsThus, NHE6 is critical for proper expression and trafficking of GLUT4. Basal expression of both insulin receptor and GLUT4 in NHE6 knockdown cells could be restored by bafilomycin-inhibition of the H+-ATPase or the H+ ionophore monensin pointing to pH dysregulation as the underlying defect. We suggest that NHE6 is a component of GLUT4 storage vesicles where it regulates proteostasis. These findings establish NHE6 as a novel contributor to glucose homeostasis and energy metabolism with implications for Christianson syndrome patients who carry loss of function mutations in the SLC9A6 gene. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/551163v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@f6fc88org.highwire.dtl.DTLVardef@13d7faforg.highwire.dtl.DTLVardef@89d577org.highwire.dtl.DTLVardef@11da50a_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2023

RIBO-former: leveraging ribosome profiling information to improve the detection of translated open reading frames.

AO_SCPLOWBSTRACTC_SCPLOWRibosome profiling is a deep sequencing technique used to chart translation by means of mRNA ribosome occupancy. It has been instrumental in the detection of non-canonical coding sequences. Because of the complex nature of next-generation sequencing data, existing solutions that seek to identify translated open reading frames from the data are still not perfect. We propose RIBO-former, a new approach featuring several innovations for the de novo annotation of translated coding sequences. RIBO-former is built using recent transformer models that have achieved considerable advancements in the field of natural language processing. The presented deep learning approach allows to omit several pre-processing steps as features are automatically extracted from the data. We discuss various steps that improve the detection of coding sequences and show that read length information of all mapped reads can be leveraged to improve the predictive performance of the tool. Our results show RIBO-former to outperform previous methodologies. Additionally, through our study we find support for the existence of translated non-canonical ORFs, present along existing coding sequences or on long non-coding RNAs. Furthermore, several polycistronic mRNAs with multiple translated coding regions were detected.

bioinformatics↗

bioRxiv2023

Dendritic spine neck plasticity controls synaptic expression of long-term potentiation

Dendritic spines host glutamatergic excitatory synapses and compartmentalize biochemical signalling underlying synaptic plasticity. The narrow spine neck that connects the spine head with its parent dendrite is the crucial structural element of this compartmentalization. Both neck morphology and its molecular composition differentially regulate exchange of molecular signals between the spine and rest of the neuron. Although these spine neck properties themselves show activity-dependent plasticity, it remains unclear what functional role spine neck plasticity plays in synaptic plasticity expression. To address this, we built a data-constrained biophysical computational model of AMPA receptor (AMPAR) trafficking and intracellular signalling involving Ca2+/calmodulin-dependent kinase II (CaMKII) and the phosphatase calcineurin in hippocampal CA1 neurons, which provides new mechanistic insights into spatiotemporal AMPAR dynamics during long-term potentiation (LTP). Using the model, we tested how plasticity of neck morphology and of neck septin7 barrier, which specifically restricts membrane protein diffusion, affect LTP. We found that spine neck properties control LTP by regulating the balance between AMPAR and calcineurin escape from the spine. Neck plasticity that increases spine-dendrite coupling reduces LTP by allowing more AMPA receptors to diffuse away from the synapse. Surprisingly, neck plasticity that decreases spine-dendrite coupling can also reduce LTP by trapping calcineurin, which dephosphorylates AMPARs. Further simulations showed that the precise timescale of neck plasticity, relative to AMPAR and enzyme diffusion and phosphorylation dynamics, critically regulates LTP. These results suggest a new mechanistic and experimentally-testable theory for how spine neck plasticity regulates synaptic plasticity.

neuroscience↗

bioRxiv2022

HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes

Existing methods for simulating synthetic genotype and phenotype datasets have limited scalability, constraining their usability for large-scale analyses. Moreover, a systematic approach for evaluating synthetic data quality and a benchmark synthetic dataset for developing and evaluating methods for polygenic risk scores are lacking. We present HAPNEST, a novel approach for efficiently generating diverse individual-level genotypic and phenotypic data. In comparison to alternative methods, HAPNEST shows faster computational speed and a lower degree of relatedness with reference panels, while generating datasets that preserve key statistical properties of real data. These desirable synthetic data properties enabled us to generate 6.8 million common variants and nine phenotypes with varying degrees of heritability and polygenicity across 1 million individuals. We demonstrate how HAPNEST can facilitate biobank-scale analyses through the comparison of seven methods to generate polygenic risk scoring across multiple ancestry groups and different genetic architectures.

bioinformatics↗

bioRxiv2022

Identification of leaf rust resistance loci in a geographically diverse panel of wheat using genome-wide association analysis

Leaf rust, caused by Puccinia triticina (Pt) is among the most devastating diseases posing a significant threat to global wheat production. The continuously evolving virulent Pt races in North America calls for exploring new sources of leaf rust resistance. A diversity panel of 365 bread wheat accessions selected from a worldwide population of landraces and cultivars was evaluated at the seedling stage against four Pt races (TDBJQ, TBBGS, MNPSD and, TNBJS). A wide distribution of seedling responses against the four Pt races was observed. Majority of the genotypes displayed a susceptible response with only 28 (9.8%), 59 (13.5%), 45 (12.5%), and 29 (8.1%) wheat accessions exhibiting a highly resistant response to TDBJQ, TBBGS, MNPSD and, TNBJS, respectively. Further, we conducted a high-resolution multi-locus genome-wide association study (GWAS) using a set of 302,524 high-quality single nucleotide polymorphisms (SNPs). The GWAS analysis identified 27 marker-trait associations (MTAs) for leaf rust resistance on different wheat chromosomes of which 20 MTAs were found in the vicinity of known Lr genes, MTAs, or quantitative traits loci (QTLs) identified in previous studies. The remaining seven significant MTAs identified represent genomic regions that harbor potentially novel genes for leaf rust resistance. Furthermore, the candidate gene analysis for the significant MTAs identified various genes of interest that may be involved in disease resistance. The identified resistant lines and SNPs linked to the QTLs in this study will serve as valuable resources in wheat rust resistance breeding programs.

plant biology↗

bioRxiv2022

Photonic-Plasmonic Coupling Enhanced Fluorescence Enabling Digital-Resolution Ultrasensitive Protein Detection

Assays utilizing molecular fluorophores are common throughout life science research and diagnostic testing, although detection limits are generally limited by weak emission intensity, thus requiring many labeled target molecules to combine their output to achieve signal-to-noise greater than the background. Here, we describe how the synergistic coupling of plasmonic and photonic resonance modes can significantly boost the emission from fluorescent dye molecules without increasing the illumination intensity while utilizing a microscopy approach with a broad field of view. By optimally matching the resonant modes of a plasmonic fluor (PF) nanoparticle and a photonic crystal (PC) surface with the absorption and emission spectrum of the PFs fluorescent dye, we observe a 52-fold improvement in signal intensity, enabling individual PFs to be observed and digitally counted, using an approach in which one PF tag represents detection of one target molecule. The photonic amplification from the PF can be attributed to the strong near-field enhancement due to the cavity-induced activation of the PF, PC band structure-mediated improvement in collection efficiency of emitted photons, and increased rate of spontaneous emission. We demonstrate the applicability of the method by dose-response characterization of a sandwich immunoassay for human interleukin-6, a biomarker commonly used to assist diagnosis of cancer, inflammation, sepsis, and autoimmune disease. We achieve a limit of detection of 10 fg/ml, representing a capability three orders of magnitude lower than standard immunoassays.

bioengineering↗

bioRxiv2022

Pleiotropic roles for mycobacterial DinB2 in frameshift and substitution mutagenesis

Translesion synthesis mediated by translesion polymerases is a conserved mechanism of DNA damage tolerance. In bacteria, DinB enzymes are widely distributed promutagenic translesion polymerases. The role of DinBs in mycobacterial mutagenesis was unclear until recent studies revealed a role for mycobacterial DinB1 in substitution and frameshift mutagenesis, overlapping with that of translesion polymerase DnaE2. M. smegmatis encodes two additional DinBs (DinB2 and DinB3) and M. tuberculosis encodes DinB2, but the roles of these polymerases in mycobacterial damage tolerance and mutagenesis is unknown. The biochemical properties of DinB2, including facile utilization of ribonucleotides and 8-oxo-guanine, suggest that DinB2 could be a promutagenic polymerase. Here we examine the effects of DinB2 and DinB3 overexpression in mycobacterial cells. We demonstrate that DinB2 can drive diverse substitution mutations conferring antibiotic resistance. DinB2 induces frameshift mutations in homopolymeric sequences, both in vitro and in vivo. DinB2 switches from less to more mutagenic in the presence of manganese in vitro. This study indicates that DinB2 may contribute to mycobacterial mutagenesis and antibiotic resistance acquisition in combination with DinB1 and DnaE2.

microbiology↗

bioRxiv2022

Neuronal Maturation-dependent Nano-Neuro Interaction and Modulation

Nanotechnology-enabled neuromodulation, a rapidly growing technique, is a promising minimally-invasive tool in neuroscience and engineering for both fundamental studies as well as clinical applications. However, the nano-neuro interactions at different stages of maturation of a neural network and its implications on the nano-neuromodulation remain unclear. Here, we report heterogeneous to homogenous transformation of neuromodulation in a progressively maturing neural network. Utilizing plasmonic fluors as ultrabright fluorescent nanolabels, we reveal that negative surface charge of the nanoparticles renders selective nano-neuro interaction with a strong correlation between the maturation stage of the individual neurons in the neural network and the density of the nanoparticles bound on the neurons. In stark contrast to homogeneous neuromodulation in a mature neural network reported so far, the maturation-dependent density of the nanoparticles bound to neurons in a developing neural network resulted in a heterogeneous optical neuromodulation (i.e., simultaneous excitation and inhibition of neural network activity). This study advances our understanding of nano-neuro interactions and nano-neuromodulation with potential applications in minimally-invasive technologies for treating neuronal disorders in parts of mammalian brain where neurogenesis persists throughout aging.

bioengineering↗

bioRxiv2022

Immunity priming uncouples the growth-defense tradeoff in tomato

Plants have developed an array of mechanisms to protect themselves against pathogen invasion. The deployment of defense mechanisms is imperative for plant survival, but can come at the expense of plant growth, leading to the "growth- defense trade-off" phenomenon. Following pathogen exposure, plants can develop resistance to further attack. This is known as induced resistance, or priming. Here, we investigated the growth-defense trade-off, examining how defense priming via Systemic Acquired Resistance (SAR), or Induced Systemic Resistance (ISR), affects tomato development and growth. We found that defense priming can promote, rather than inhibit, plant development, and that defense priming and growth tradeoffs can be uncoupled. Cytokinin response was activated during induced resistance, and found to be required for the observed growth and disease resistance resulting from ISR activation. ISR was found to have a stronger effect on plant development than SAR. Our results suggest that growth promotion and induced resistance can be co-dependent, and that in certain cases, defense priming can drive developmental processes and promote plant yield. Summary statementGrowth-defense tradeoffs in plants result in loss of yield. Here, we demonstrate that immunity priming in different pathways uncouples this tradeoff and allows for disease resistant plants with robust growth.

plant biology↗

bioRxiv2022

Small molecule mediated stabilization of PP2A modulates the Homologous Recombination pathway and potentiates DNA damage-induced cell death

High-Grade Serous Carcinoma (HGSC) is the most common and lethal ovarian cancer subtype. PARP-inhibitors (PARPi) have become the mainstay of HGSC targeted therapy, given that these tumors are driven by a high degree of genomic instability and Homologous Recombination (HR) defects. Nonetheless, only [~]30% of patients initially respond to treatment, ultimately relapsing with resistant disease. Thus, despite recent advances in drug development and increased understanding of genetic alterations driving HGSC progression, mortality has not declined, highlighting the need for novel therapies. Using a Small Molecule Activator of Protein Phosphatase 2A (PP2A) (SMAP-061), we investigated the mechanism by which PP2A stabilization induces apoptosis in Patient-Derived HGSC cells and Xenograft (PDX) models alone or in combination with PARPi. We uncovered that PP2A genes essential for transformation (B56,B56{gamma} and PR72) and basal phosphatase activity (PP2A-A and -C) are heterozygously lost in the majority of HGSC. Moreover, loss of these PP2A genes correlates with worse overall patient survival. We show that SMAP-061 stabilization of PP2A inhibits the HR output by targeting RAD51, leading to chronic accumulation of DNA damage and ultimately apoptosis. Furthermore, combination of SMAP-061 and PARPi leads to enhanced apoptosis in both HR-proficient and -deficient cells and in patient-derived xenograft models. Our studies identify PP2A as novel regulator of HR and introduces PP2A activators as a potential treatment for HGSC tumors. Our studies further emphasize the potential of PP2A modulators to overcome PARPi insensitivity, given that targeting RAD51 has presented benefits in overcoming PARPi-resistance driven by BRCA1/2 mutation reversions.

cancer biology↗

bioRxiv2022

Optimization of a Translational Murine Model of Closed-head Traumatic Brain Injury

Traumatic brain injury (TBI) from closed-head trauma is a leading cause of disability with limited effective interventions. Many TBI models impact brain parenchyma directly following craniotomy, and are limited by the fact that these forces do not recapitulate clinically relevant closed head injury. However, applying clinically relevant injury mechanics to an intact skull may lead to variability and as a result, modeling TBI remains a challenge. Moreover, current models often do not explore sex differences in TBI, which is critically important for translation to clinical practice. We systematically investigated sources of variability in a murine model of closed-head TBI and developed a framework to reduce variability across severity and sex. We manipulated pressure, dwell time, and displacement to determine effects on vestibulomotor performance, spatial learning, and neuronal damage in 10-week-old male and female mice. Increasing pressure beyond 70psi had a ceiling effect on cellular and behavioral outcomes, while manipulating dwell time only affected behavioral performance. Increasing displacement precisely graded injury severity in both sexes across all outcomes. Physical signs of trauma occurred more frequently at higher displacements. Females performed worse than males when injured at 2.7mm displacement, and had greater mortality at higher displacements. Stratifying severity based on day-1 rotarod performance retained cellular injury relationships and separated both sexes into injury severity cohorts with distinct behavioral recovery. Utilizing this stratification strategy, within-group rotarod variability over 6 days post-injury was reduced by 50%. These results have important implications for translational research in TBI and provide a framework for using this clinically relevant translational injury model in both male and female mice.

neuroscience↗

bioRxiv2022

SARS-CoV-2 Omicron Variant Wave in India: Advent, Phylogeny and Evolution

SARS-CoV-2 evolution has continued to generate variants, responsible for new pandemic waves locally and globally. Varying disease presentation and severity has been ascribed to inherent variant characteristics and vaccine immunity. This study analyzed genomic data from 305 whole genome sequences from SARS-CoV-2 patients before and through the third wave in India. Delta variant was responsible for disease in patients without comorbidity(97%), while Omicron BA.2 caused disease primarily in those with comorbidity(77%). Tissue adaptation studies brought forth higher propensity of Omicron variants to bronchial tissue than lung, contrary to observation in Delta variants from Delhi. Study of codon usage pattern distinguished the prevalent variants, clustering them separately, Omicron BA.2 isolated in February grouped away from December strains, and all BA.2 after December acquired a new mutation S959P in ORF1b (44.3% of BA.2 in the study) indicating ongoing evolution. Loss of critical spike mutations in Omicron BA.2 and gain of immune evasion mutations including G142D, reported in Delta but absent in BA.1, and S371F instead of S371L in BA.1 could possibly be due to evolutionary trade-off and explain very brief period of BA.1 in December 2021, followed by complete replacement by BA.2.

genomics↗