Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain.

The continual evolution of SARS-CoV-2 and the emergence of variants that show resistance to vaccines and neutralizing antibodies threaten to prolong the COVID-19 pandemic. Selection and emergence of SARS-CoV-2 variants are driven in part by mutations within the viral spike protein and in particular the ACE2 receptor-binding domain (RBD), a primary target site for neutralizing antibodies. Here, we develop deep mutational learning (DML), a machine-learning-guided protein engineering technology, which is used to investigate a massive sequence space of combinatorial mutations, representing billions of RBD variants, by accurately predicting their impact on ACE2 binding and antibody escape. A highly diverse landscape of possible SARS-CoV-2 variants is identified that could emerge from a multitude of evolutionary trajectories. DML may be used for predictive profiling on current and prospective variants, including highly mutated variants such as Omicron, thus guiding the development of therapeutic antibody treatments and vaccines for COVID-19.

A functional cellular framework for sex and estrous cycle-dependent gene expression and behavior.

Sex hormones exert a profound influence on gendered behaviors. How individual sex hormone-responsive neuronal populations regulate diverse sex-typical behaviors is unclear. We performed orthogonal, genetically targeted sequencing of four estrogen receptor 1-expressing (Esr1+) populations and identified 1,415 genes expressed differentially between sexes or estrous states. Unique subsets of these genes were distributed across all 137 transcriptomically defined Esr1+ cell types, including estrous stage-specific ones, that comprise the four populations. We used differentially expressed genes labeling single Esr1+ cell types as entry points to functionally characterize two such cell types, BNSTprTac1/Esr1 and VMHvlCckar/Esr1. We observed that these two cell types, but not the other Esr1+ cell types in these populations, are essential for sex recognition in males and mating in females, respectively. Furthermore, VMHvlCckar/Esr1 cell type projections are distinct from those of other VMHvlEsr1 cell types. Together, projection and functional specialization of dimorphic cell types enables sex hormone-responsive populations to regulate diverse social behaviors.

N6-methyladenosine in 5' UTR does not promote translation initiation.

The most abundant N6-methyladenosine (m6A) modification on mRNAs is installed non-stoichiometrically across transcripts, with 5' untranslated regions (5' UTRs) being the least conductive. 5' UTRs are essential for translation initiation, yet the molecular mechanisms orchestrated by m6A remain poorly understood. Here, we combined structural, biochemical, and single-molecule approaches and show that at the most common position, a single m6A does not affect translation yields, the kinetics of translation initiation complex assembly, or start codon recognition both under permissive growth and following exposure to oxidative stress. Cryoelectron microscopy (cryo-EM) structures of the late preinitiation complex reveal that m6A purine ring established stacking interactions with an arginine side chain of the initiation factor eIF2α, although with only a marginal energy contribution, as estimated computationally. These findings provide molecular insights into m6A interactions with the initiation complex and suggest that the subtle stabilization is unlikely to affect the translation dynamics under homeostatic conditions or stress.

High-throughput T cell receptor engineering by functional screening identifies candidates with enhanced potency and specificity.

A major challenge in adoptive T cell immunotherapy is the discovery of natural T cell receptors (TCRs) with high activity and specificity to tumor antigens. Engineering synthetic TCRs for increased tumor antigen recognition is complicated by the risk of introducing cross-reactivity and by the poor correlation that can exist between binding affinity and activity of TCRs in response to antigen (peptide-MHC). Here, we developed TCR-Engine, a method combining genome editing, computational design, and deep sequencing to engineer the functional activity and specificity of TCRs on the surface of a human T cell line at high throughput. We applied TCR-Engine to successfully engineer synthetic TCRs for increased potency and specificity to a clinically relevant tumor-associated antigen (MAGE-A3) and validated their translational potential through multiple in vitro and in vivo assessments of safety and efficacy. Thus, TCR-Engine represents a valuable technology for engineering of safe and potent synthetic TCRs for immunotherapy applications.

Capture RIC-seq reveals positional rules of PTBP1-associated RNA loops in splicing regulation.

RNA-binding proteins (RBPs) bind at different positions of the pre-mRNA molecules to promote or reduce the usage of a particular exon. Seeking to understand the working principle of these positional effects, we develop a capture RIC-seq (CRIC-seq) method to enrich specific RBP-associated in situ proximal RNA-RNA fragments for deep sequencing. We determine hnRNPA1-, SRSF1-, and PTBP1-associated proximal RNA-RNA contacts and regulatory mechanisms in HeLa cells. Unexpectedly, the 3D RNA map analysis shows that PTBP1-associated loops in individual introns preferentially promote cassette exon splicing by accelerating asymmetric intron removal, whereas the loops spanning across cassette exon primarily repress splicing. These "positional rules" can faithfully predict PTBP1-regulated splicing outcomes. We further demonstrate that cancer-related splicing quantitative trait loci can disrupt RNA loops by reducing PTBP1 binding on pre-mRNAs to cause aberrant splicing in tumors. Our study presents a powerful method for exploring the functions of RBP-associated RNA-RNA proximal contacts in gene regulation and disease.

High-Resolution Whole-Genome Analysis of Sister-Chromatid Contacts.

Sister-chromatid cohesion describes the orderly association of newly replicated DNA molecules behind replication forks. It plays an essential role in the maintenance and faithful transmission of genetic information. Cohesion is created by DNA topological links and proteinaceous bridges, whose formation and deposition could be potentially affected by many processes. Current knowledge on cohesion has been mainly gained by fluorescence microscopy observation. However, the resolution limit of microscopy and the restricted number of genomic positions that can be simultaneously visualized considerably hampered progress. Here, we present a high-throughput methodology to monitor sister-chromatid contacts (Hi-SC2). Using the multi-chromosomal Vibrio cholerae bacterium as a model, we show that Hi-SC2 permits to monitor local variations in sister-chromatid cohesion at a high resolution over a whole genome.

High-throughput approaches to understand and engineer bacteriophages.

Bacteriophage research has been vital to fundamental aspects of modern biology. Advances in metagenomics have revealed treasure troves of new and uncharacterized bacteriophages ('phages') that are not yet understood. However, our ability to find new phages has outpaced our understanding of how sequence encodes function in phages. Traditional approaches for characterizing phages are limited in scale and face hurdles in determining how changes in sequence drive function. We describe powerful emerging technologies that can be used to clarify sequence-function relationships in phages through high-throughput genome engineering. Using these approaches, up to 105 variants can be characterized through pooled selection experiments and deep sequencing. We describe caveats when using these tools and provide examples of basic science and engineering goals that are pursuable using these approaches.

Mapping Degradation Signals and Pathways in a Eukaryotic N-terminome.

Most eukaryotic proteins are N-terminally acetylated. This modification can be recognized as a signal for selective protein degradation (degron) by the N-end rule pathways. However, the prevalence and specificity of such degrons in the proteome are unclear. Here, by systematically examining how protein turnover is affected by N-terminal sequences, we perform a comprehensive survey of degrons in the yeast N-terminome. We find that approximately 26% of nascent protein N termini encode cryptic degrons. These degrons exhibit high hydrophobicity and are frequently recognized by the E3 ubiquitin ligase Doa10, suggesting a role in protein quality control. In contrast, N-terminal acetylation rarely functions as a degron. Surprisingly, we identify two pathways where N-terminal acetylation has the opposite function and blocks protein degradation through the E3 ubiquitin ligase Ubr1. Our analysis highlights the complexity of N-terminal degrons and argues that hydrophobicity, not N-terminal acetylation, is the predominant feature of N-terminal degrons in nascent proteins.

Single-cell phenotyping of bacteria combined with deep sequencing for improved contextualization of microbiome analyses.

Great effort was made to characterize the bacterial communities inhabiting the human body as a factor in disease, resulting in the realization that a wide spectrum of diseases is associated with an altered composition of the microbiome. However, the identification of disease-relevant bacteria has been hindered by the high cross-sectional diversity of individual microbiomes, and in most cases, it remains unclear whether the observed alterations are cause or consequence of disease. Hence, innovative analysis approaches are required that enable inquiries of the microbiome beyond mere taxonomic cataloging. This review highlights the utility of microbiota flow cytometry, a single-cell analysis platform to directly interrogate cellular interactions, cell conditions, and crosstalk with the host's immune system within the microbiome to take into consideration the role of microbes as critical interaction partners of the host and the spectrum of microbiome alterations, beyond compositional changes. In conjunction with advanced sequencing approaches it could reveal the genetic potential of target bacteria and advance our understanding of taxonomic diversity and gene usage in the context of the microenvironment. Single-cell bacterial phenotyping has the potential to change our perspective on the human microbiome and empower microbiome research for the development of microbiome-based therapy approaches and personalized medicine.

Enrichment reveals extensive integration of hepatitis B virus DNA in hepatitis delta-infected patients.

INTRODUCTION: Hepatitis B virus (HBV) DNA may become integrated into the human genome of infected human hepatocytes. Expression of integrations can produce the surface antigen (HBsAg) that is required for synthesis of hepatitis D virus (HDV) particles and the abundant subviral particles in the blood of HBV- and HDV-infected subjects. Knowledge about the extent and variation of HBV integrations and impact on chronic HDV is still limited. METHODS: We investigated 50 pieces of liver explant tissue from five patients with hepatitis D-induced cirrhosis, using a deep sequencing strategy targeting HBV RNA. RESULTS: We found that integrations were abundant and highly expressed, however with large variation in number of integration derived (HBV/human chimeric) reads, both between and within patients. The median number of unique integrations for each patient correlated with serum levels of both HBsAg. Still, most of the HBV reads represented a few predominant integrations. CONCLUSIONS: The results suggest that HBV DNA integrates in a large proportion of hepatocytes, and that the HBsAg output from these integrations vary >100-fold depending on clone size and expression rate. A small part of the integrations seems to determine the serum levels of HBsAg and HDV RNA in HBV/HDV co-infected patients with liver cirrhosis.

Improved Prediction of Stabilizing Mutations in Proteins by Incorporation of Mutational Effects on Ligand Binding.

While many computational methods accurately predict destabilizing mutations, identifying stabilizing mutations has remained a challenge, because of their relative rarity. We tested ΔΔG0 predictions from computational predictors such as Rosetta, ThermoMPNN, RaSP, and DeepDDG, using 82 mutants of the bacterial toxin CcdB as a test case. On this dataset, the best computational predictor is ThermoMPNN, which identifies stabilizing mutations with a precision of 68%. However, the average increase in Tm for these predicted mutations was only 1°C for CcdB, and predictions were poorer for a more challenging target, influenza neuraminidase. Using data from multiple previously described yeast surface display libraries and in vitro thermal stability measurements, we trained logistic regression models to identify stabilizing mutations with a precision of 90% and an average increase in Tm of 3°C for CcdB. When such libraries contain a population of mutants with significantly enhanced binding relative to the corresponding wild type, there is no benefit in using computational predictors. It is then possible to predict stabilizing mutations without any training, simply by examining the distribution of mutational binding scores. This avoids laborious steps of in vitro expression, purification, and stability characterization. When this is not the case, combining data from computational predictors with high-throughput experimental binding data enhances the prediction of stabilizing mutations. However, this requires training on stability data measured in vitro with known stabilized mutants. It is thus feasible to predict stabilizing mutations rapidly and accurately for any system of interest that can be subjected to a binding selection or screen.

A simple, rapid, and efficient method for generating multigene-knockout culture cells by the CRISPR/Cas9 system.

We evaluated the efficacy of simultaneous multiple-gene knockout in human culture cells. By simple co-transfection of HeLa cells with a mixture of pX330-based targeting plasmids together with a puromycin resistance plasmid, followed by transient selection of puromycin-resistant cells, Cas9/single-guide RNA (sgRNA)-transduced polyclonal cell populations were selected and grown. Western blot analyses revealed co-transfection of up to seven targeting plasmids for p38α, p38ß, JNK1, JNK2, Mnk1, ERK1, and mLST8 genes, drastically reduced protein expression of these genes in the polyclonal population. Analyses of a randomly isolated group of 25 clones revealed knockout efficiencies for the seven targeted genes ranging between 68% and 100%, and in six clones (24%), all targeted genes were disrupted. Deep sequencing analyses of the individual target sites revealed that, in most cases, Cas9/sgRNA-induced nonhomologous end joining resulted in deletion or insertion of only a few base pairs at the break points. These results demonstrate that simple co-transfection-based simultaneous targeting offers an easy, rapid, and efficient method to generate multiplex gene-knockout cell lines.

Tailer: a pipeline for sequencing-based analysis of nonpolyadenylated RNA 3' end processing.

Post-transcriptional trimming and tailing of RNA 3' ends play key roles in the processing and quality control of noncoding RNAs (ncRNAs). However, bioinformatic tools to examine changes in the RNA 3' "tailome" are sparse and not standardized. Here we present Tailer, a bioinformatic pipeline in two parts that allows for robust quantification and analysis of tail information from next-generation sequencing experiments that preserve RNA 3' end information. The first part of Tailer, Tailer-processing, uses genome annotation or reference FASTA gene sequences to quantify RNA 3' ends from SAM-formatted alignment files or FASTQ sequence read files produced from sequencing experiments. The second part, Tailer-analysis, uses the output of Tailer-processing to identify statistically significant RNA targets of trimming and tailing and create graphs for data exploration. We apply Tailer to RNA 3' end sequencing experiments from three published studies and find that it accurately and reproducibly recapitulates key findings. Thus, Tailer should be a useful and easily accessible tool to globally investigate tailing dynamics of nonpolyadenylated RNAs and conditions that perturb them.

Puzzles, challenges, and information reservoir of SARS-CoV-2 quasispecies.

Upon the emergence of SARS-CoV-2 in the human population, it was conjectured that for this coronavirus the dynamic intra-host heterogeneity typical of RNA viruses would be toned down. Nothing of this sort is observed. Here we review the main observations on the complexity and diverse composition of SARS-CoV-2 mutant spectra sampled from infected patients, within the framework of quasispecies dynamics. The analyses suggest that the information provided by myriads of genomic sequences within infected individuals may have a predictive value of the genomic sequences that acquire epidemiological relevance. Possibilities to reconcile the presence of broad mutant spectra in the large RNA coronavirus genome with its encoding a 3' to 5' exonuclease proofreading-repair activity are considered. Indeterminations in the behavior of individual viral genomes provide a benefit for the survival of the ensemble. We propose that this concept falls in the domain of "stochastic thinking," a notion that applies also to cellular processes, as a means for biological systems to face unexpected needs.

The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design.

Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, streamlining the process of Ab discovery, engineering, and development. These artificially engineered Abs offer novel approaches to antigen recognition, paratope site manipulation, and biochemical/biophysical enhancements. As a result, synthetic Abs are fundamentally reshaping conventional methods of Ab production. This mirrors the revolution observed in molecular biology and genomics as a result of deep sequencing, which allows for the swift and cost-effective sequencing of DNA and RNA molecules at scale. Within this framework, deep sequencing has enabled the exploration of whole genomes and transcriptomes, including particular gene segments of interest. Notably, the fusion of synthetic Ab discovery with advanced deep sequencing technologies is redefining the current approaches to Ab design and development. Such combination offers opportunity to exhaustively explore Ab repertoires, fast-tracking the Ab discovery process, and enhancing synthetic Ab engineering. Moreover, advanced computational algorithms have the capacity to effectively mine big data, helping to identify Ab sequence patterns/features hidden within deep sequencing Ab datasets. In this context, these methods can be utilized to predict novel sequence features thereby enabling the successful generation of de novo Ab molecules. Hence, the merging of synthetic Ab design, deep sequencing technologies, and advanced computational models heralds a new chapter in Ab discovery, broadening our comprehension of immunology and streamlining the advancement of biological therapeutics.

Genotyping Plasmodium falciparum gametocytes using amplicon deep sequencing.

BACKGROUND: Understanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing. METHODS: A data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum. Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach. RESULTS: A 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92-0.99] and 0.92 [95% CI: 0.83-0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28-0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35-3.68]. CONCLUSIONS: A region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

Global and single-nucleotide resolution detection of 7-methylguanosine in RNA.

RNA modifications, including N-7-methylguanosine (m7G), are pivotal in governing RNA stability and gene expression regulation. The accurate detection of internal m7G modifications is of paramount significance, given recent associations between altered m7G deposition and elevated expression of the methyltransferase METTL1 in various human cancers. The development of robust m7G detection techniques has posed a significant challenge in the field of epitranscriptomics. In this study, we introduce two methodologies for the global and accurate identification of m7G modifications in human RNA. We introduce borohydride reduction sequencing (Bo-Seq), which provides base resolution mapping of m7G modifications. Bo-Seq achieves exceptional performance through the optimization of RNA depurination and scission, involving the strategic use of high concentrations of NaBH4, neutral pH and the addition of 7-methylguanosine monophosphate (m7GMP) during the reducing reaction. Notably, compared to NaBH4-based methods, Bo-Seq enhances the m7G detection performance, and simplifies the detection process, eliminating the necessity for intricate chemical steps and reducing the protocol duration. In addition, we present an antibody-based approach, which enables the assessment of m7G relative levels across RNA molecules and biological samples, however it should be used with caution due to limitations associated with variations in antibody quality between batches. In summary, our novel approaches address the pressing need for reliable and accessible methods to detect RNA m7G methylation in human cells. These advancements hold the potential to catalyse future investigations in the critical field of epitranscriptomics, shedding light on the complex regulatory roles of m7G in gene expression and its implications in cancer biology.

First Report of Sweet Potato Virus E(SPVE) Infecting Sweet Potato in China.

Sweet potato (Ipomoea batatas [L.] Lam.) is a versatile crop, cultivated in the subtropical and tropical areas, as food, fodder, and industrial raw material crop. In China, sweet potato has been used as a health-care food in recent years, as it contains a wide range of nutrients and xenobiotic phytochemicals. However, viral diseases are major constraint for the sweet potato yield and quality, especially the seed production and quality. Over 30 species of viruses infect sweet potato worldwide (Clark et al. 2012). More recently, a few new viruses infected sweet potato were identified, such as sweet potato virus E (SPVE), which was reported in Korea(Jo et al. 2020). In May 2022, a sweet potato sample (JSXZ1) with virus-like symptom, such as mosaic and vein clearing were collected from sweet potato germplasm Xuzhou resource nursery, Jiangsu Province, China (N34˚16', E117˚18') (Fig. S1A). To investigate the virus disease, the sample JSXZ1 showing the typical symptoms of disease was prepared for Small-RNA (sRNA) deep-sequencing. The sRNA library was constructed using TruSeq™ Small RNA Sample Prep Kits (Illumina, San Diego, USA) and sequenced using the Illumine Hiseq 2500 platform by LC-Bop Technologies (Hangzhou) CO., LTD. The sample was sequenced to obtain 26, 358, 439 raw reads and 22, 969, 139 clean reads after quality control trimming and analysis. The Velvet 1.0.5 software was used to de novo assemble the clean reads (18 to 28 nt) into larger contigs, which were then compared with the nucleotide sequences in the National Center for Biotechnology Information (NCBI) database using the BLASTn algorithm. Viruses found in the sample were sweet potato latent virus (SPLV), sweet potato feathery mottle virus (SPFMV), sweet potato chlorotic stunt virus (SPCSV), sweet potato badnavirus A (SPBV-A) and sweet potato badnavirus B (SPBV-B). Surprisingly, besides the viruses listed above, 28 contigs matched sequences of SPVE isolate GS (MH388502). To verify the result, total RNA was extracted from the sample JSXZ1 and from other leave samples (JSXZ2-JSXZ5) that contained SPFMV, SPVC, SPLV, SPVG respectively stored in lab using FastPure Universal Plant Total RNA Isolation Kit (Vazyme Biotech Co., LTD, Nanjing, China). cDNA was synthesized using random primer (hexadeoxyribonucleotide mixture; pd(N)6). The cDNA serves as template in PCR using a newly designed primer pairs based on SPVE p1 gene (SPVE-F: 5'- TCACCAAAAAGAATGCTACAAC-3'/SPVE-R: 5'-GAAATCCTCCCACTCTCCATA-3'). An expected ~500-bp PCR fragment was obtained in JSXZ1, while none of the fragment was obtained from JSXZ2-JSXZ5 (Fig. S1B). The PCR fragment was cloned into pMD18-T vector (Takara Bio Inc., Beijing, China) and plasmid DNA from transformed Escherichia coli DH5α cell (n=3) were commercially sequenced by Sangon Biotech (Shanghai) Co., Ltd. The sequences of the three fragment clones we obtained were 100% identical when compared. A BLASTN analysis of the sequences revealed that they are specific to SPVE and shared 98.62% nucleotide identity to SPVE GS isolate (MH388502) and one sequence was submitted to GenBank (Accession number OQ948331). To determine the occurrence of SPVE in infected sweet potato plants, a total of 37 leaves samples with viral symptom collected from Shandong Province (n=6) and Jiangsu Province (n=31) were indexed by RT-PCR as described before. Only 9 (24.3%) out of 37 from Shandong (n=1) and Jiangsu (n=8) were positive to SPVE respectively. In addition, five additional viruses (SPFMV, SPVC, SPVG, SPLV, SPCSV) were detected among these 37 samples and always in a mixed infection of two or more viruses. To our knowledge, this is the first report of SPVE infecting sweet potato in China. Sweet potato is an important crop in China and other countries (Zhang et al. 2023). China is the largest sweet potato producer all over the world. In addition, as sweet potato is produced through the vegetative propagation mode, thus, more attention should be paid to detection and monitoring of occurrence of SPVE in China.

Amplicon Deep Sequencing Reveals Multiple Genetic Events Lead to Treatment Failure with Atovaquone-Proguanil in Plasmodium falciparum.

Atovaquone-proguanil (AP) is used as treatment for uncomplicated malaria, and as a chemoprophylactic agent against Plasmodium falciparum. Imported malaria remains one of the top causes of fever in Canadian returning travelers. Twelve sequential whole-blood samples before and after AP treatment failure were obtained from a patient diagnosed with P. falciparum malaria upon their return from Uganda and Sudan. Ultradeep sequencing was performed on the cytb, dhfr, and dhps markers of treatment resistance before and during the episode of recrudescence. Haplotyping profiles were generated using three different approaches: msp2-3D7 agarose and capillary electrophoresis, and cpmp using amplicon deep sequencing (ADS). A complexity of infection (COI) analysis was conducted. De novo cytb Y268C mutants strains were observed during an episode of recrudescence 17 days and 16 h after the initial malaria diagnosis and AP treatment initiation. No Y268C mutant reads were observed in any of the samples prior to the recrudescence. SNPs in the dhfr and dhps genes were observed upon initial presentation. The haplotyping profiles suggest multiple clones mutating under AP selection pressure (COI > 3). Significant differences in COI were observed by capillary electrophoresis and ADS compared to the agarose gel results. ADS using cpmp revealed the lowest haplotype variation across the longitudinal analysis. Our findings highlight the value of ultra-deep sequencing methods in the understanding of P. falciparum haplotype infection dynamics. Longitudinal samples should be analyzed in genotyping studies to increase the analytical sensitivity.

Rapid SARS-CoV-2 Adaptation to Available Cellular Proteases.

Recent emergence of SARS-CoV-1 variants demonstrates the potential of this virus for targeted evolution, despite its overall genomic stability. Here we show the dynamics and the mechanisms behind the rapid adaptation of SARS-CoV-2 to growth in Vero E6 cells. The selective advantage for growth in Vero E6 cells is due to increased cleavage efficiency by cathepsins at the mutated S1/S2 site. S1/S2 site also constitutes a heparan sulfate (HS) binding motif that influenced virus growth in Vero E6 cells, but HS antagonist did not inhibit virus adaptation in these cells. The entry of Vero E6-adapted virus into human cells is defective because the mutated spike variants are poorly processed by furin or TMPRSS2. Minor subpopulation that lack the furin cleavage motif in the spike protein rapidly become dominant upon passaging through Vero E6 cells, but wild type sequences are maintained at low percentage in the virus swarm and mediate a rapid reverse adaptation if the virus is passaged again on TMPRSS2+ human cells. Our data show that the spike protein of SARS-CoV-2 can rapidly adapt itself to available proteases and argue for deep sequence surveillance to identify the emergence of novel variants. IMPORTANCE Recently emerging SARS-CoV-2 variants B.1.1.7 (alpha variant), B.1.617.2 (delta variant), and B.1.1.529 (omicron variant) harbor spike mutations and have been linked to increased virus pathogenesis. The emergence of these novel variants highlights coronavirus adaptation and evolution potential, despite the stable consensus genotype of clinical isolates. We show that subdominant variants maintained in the virus population enable the virus to rapidly adapt to selection pressure. Although these adaptations lead to genotype change, the change is not absolute and genomes with original genotype are maintained in the virus swarm. Thus, our results imply that the relative stability of SARS-CoV-2 in numerous independent clinical isolates belies its potential for rapid adaptation to new conditions.