Antigenic Characterization of Circulating and Emerging SARS-CoV-2 Variants in the U.S. throughout the Delta to Omicron Waves.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into numerous lineages with unique spike mutations and caused multiple epidemics domestically and globally. Although COVID-19 vaccines are available, new variants with the capacity for immune evasion continue to emerge. To understand and characterize the evolution of circulating SARS-CoV-2 variants in the U.S., the Centers for Disease Control and Prevention (CDC) initiated the National SARS-CoV-2 Strain Surveillance (NS3) program and has received thousands of SARS-CoV-2 clinical specimens from across the nation as part of a genotype to phenotype characterization process. Focus reduction neutralization with various antisera was used to antigenically characterize 143 SARS-CoV-2 Delta, Mu and Omicron subvariants from selected clinical specimens received between May 2021 and February 2023, representing a total of 59 unique spike protein sequences. BA.4/5 subvariants BU.1, BQ.1.1, CR.1.1, CQ.2 and BA.4/5 + D420N + K444T; BA.2.75 subvariants BM.4.1.1, BA.2.75.2, CV.1; and recombinant Omicron variants XBF, XBB.1, XBB.1.5 showed the greatest escape from neutralizing antibodies when analyzed against post third-dose original monovalent vaccinee sera. Post fourth-dose bivalent vaccinee sera provided better protection against those subvariants, but substantial reductions in neutralization titers were still observed, especially among BA.4/5 subvariants with both an N-terminal domain (NTD) deletion and receptor binding domain (RBD) substitutions K444M + N460K and recombinant Omicron variants. This analysis demonstrated a framework for long-term systematic genotype to antigenic characterization of circulating and emerging SARS-CoV-2 variants in the U.S., which is critical to assessing their potential impact on the effectiveness of current vaccines and antigen recommendations for future updates.

In-field detection and characterization of B/Victoria lineage deletion variant viruses causing early influenza activity and an outbreak in Louisiana, 2019.

Background: In 2019, the Louisiana Department of Health reported an early influenza B/Victoria (B/VIC) virus outbreak. Method: As it was an atypically large outbreak, we deployed to Louisiana to investigate it using genomics and a triplex real-time RT-PCR assay to detect three antigenically distinct B/VIC lineage variant viruses. Results: The investigation indicated that B/VIC V1A.3 subclade, containing a three amino acid deletion in the hemagglutinin and known to be antigenically distinct to the B/Colorado/06/2017 vaccine virus, was the most prevalent circulating virus within the specimens evaluated (86/88 in real-time RT-PCR). Conclusion: This work underscores the value of portable platforms for rapid, onsite pathogen characterization.

Targeted amplification and genetic sequencing of the severe acute respiratory syndrome coronavirus 2 surface glycoprotein.

IMPORTANCE: The COVID-19 pandemic was accompanied by an unprecedented surveillance effort. The resulting data were and will continue to be critical for surveillance and control of SARS-CoV-2. However, some genomic surveillance methods experienced challenges as the virus evolved, resulting in incomplete and poor quality data. Complete and quality coverage, especially of the S-gene, is important for supporting the selection of vaccine candidates. As such, we developed a robust method to target the S-gene for amplification and sequencing. By focusing on the S-gene and imposing strict coverage and quality metrics, we hope to increase the quality of surveillance data for this continually evolving gene. Our technique is currently being deployed globally to partner laboratories, and public health representatives from 79 countries have received hands-on training and support. Expanding access to quality surveillance methods will undoubtedly lead to earlier detection of novel variants and better inform vaccine strain selection.

Early and Increased Influenza Activity Among Children - Tennessee, 2022-23 Influenza Season.

Influenza seasons typically begin in October and peak between December and February (1); however, the 2022-23 influenza season in Tennessee began in late September and was characterized by high pediatric hospitalization rates during November. This report describes a field investigation conducted in Tennessee during November 2022, following reports of increasing influenza hospitalizations. Data from surveillance networks, patient surveys, and whole genome sequencing of influenza virus specimens were analyzed to assess influenza activity and secondary illness risk. Influenza activity increased earlier than usual among all age groups, and rates of influenza-associated hospitalization among children were high in November, reaching 12.6 per 100,000 in children aged <5 years, comparable to peak levels typically seen in high-severity seasons. Circulating influenza viruses were genetically similar to vaccine components. Among persons who received testing for influenza at outpatient clinics, children were twice as likely to receive a positive influenza test result as were adults. Among household contacts exposed to someone with influenza, children were more than twice as likely to become ill compared with adults. As the influenza season continues, it is important for all persons, especially those at higher risk for severe disease, to protect themselves from influenza. To prevent influenza and severe influenza complications, all persons aged ≥6 months should get vaccinated, avoid contact with ill persons, and take influenza antivirals if recommended and prescribed.

Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and identification of SARS-CoV-2 variants.

The coronavirus disease 2019 (COVID-19) pandemic has demonstrated a clear need for high-throughput, multiplexed and sensitive assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses and their emerging variants. Here, we present a cost-effective virus and variant detection platform, called microfluidic Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (mCARMEN), which combines CRISPR-based diagnostics and microfluidics with a streamlined workflow for clinical use. We developed the mCARMEN respiratory virus panel to test for up to 21 viruses, including SARS-CoV-2, other coronaviruses and both influenza strains, and demonstrated its diagnostic-grade performance on 525 patient specimens in an academic setting and 166 specimens in a clinical setting. We further developed an mCARMEN panel to enable the identification of 6 SARS-CoV-2 variant lineages, including Delta and Omicron, and evaluated it on 2,088 patient specimens with near-perfect concordance to sequencing-based variant classification. Lastly, we implemented a combined Cas13 and Cas12 approach that enables quantitative measurement of SARS-CoV-2 and influenza A viral copies in samples. The mCARMEN platform enables high-throughput surveillance of multiple viruses and variants simultaneously, enabling rapid detection of SARS-CoV-2 variants.

Multiplex Real-Time Reverse Transcription PCR for Influenza A Virus, Influenza B Virus, and Severe Acute Respiratory Syndrome Coronavirus 2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in late 2019, and the outbreak rapidly evolved into the current coronavirus disease pandemic. SARS-CoV-2 is a respiratory virus that causes symptoms similar to those caused by influenza A and B viruses. On July 2, 2020, the US Food and Drug Administration granted emergency use authorization for in vitro diagnostic use of the Influenza SARS-CoV-2 Multiplex Assay. This assay detects influenza A virus at 102.0, influenza B virus at 102.2, and SARS-CoV-2 at 100.3 50% tissue culture or egg infectious dose, or as few as 5 RNA copies/reaction. The simultaneous detection and differentiation of these 3 major pathogens increases overall testing capacity, conserves resources, identifies co-infections, and enables efficient surveillance of influenza viruses and SARS-CoV-2.

Epidemiologic Characteristics Associated With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen-Based Test Results, Real-Time Reverse Transcription Polymerase Chain Reaction (rRT-PCR) Cycle Threshold Values, Subgenomic RNA, and Viral Culture Results From University Testing.

BACKGROUND: Real-time reverse transcription polymerase chain reaction (rRT-PCR) and antigen tests are important diagnostics for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Sensitivity of antigen tests has been shown to be lower than that of rRT-PCR; however, data to evaluate epidemiologic characteristics that affect test performance are limited. METHODS: Paired mid-turbinate nasal swabs were collected from university students and staff and tested for SARS-CoV-2 using both Quidel Sofia SARS Antigen Fluorescent Immunoassay (FIA) and rRT-PCR assay. Specimens positive by either rRT-PCR or antigen FIA were placed in viral culture and tested for subgenomic RNA (sgRNA). Logistic regression models were used to evaluate characteristics associated with antigen results, rRT-PCR cycle threshold (Ct) values, sgRNA, and viral culture. RESULTS: Antigen FIA sensitivity was 78.9% and 43.8% among symptomatic and asymptomatic participants, respectively. Among rRT-PCR positive participants, negative antigen results were more likely among asymptomatic participants (odds ratio [OR] 4.6, 95% confidence interval [CI]: 1.3-15.4) and less likely among participants reporting nasal congestion (OR 0.1, 95% CI: .03-.8). rRT-PCR-positive specimens with higher Ct values (OR 0.5, 95% CI: .4-.8) were less likely, and specimens positive for sgRNA (OR 10.2, 95% CI: 1.6-65.0) more likely, to yield positive virus isolation. Antigen testing was >90% positive in specimens with Ct values < 29. Positive predictive value of antigen test for positive viral culture (57.7%) was similar to that of rRT-PCR (59.3%). CONCLUSIONS: SARS-CoV-2 antigen test advantages include low cost, wide availability and rapid turnaround time, making them important screening tests. The performance of antigen tests may vary with patient characteristics, so performance characteristics should be accounted for when designing testing strategies and interpreting results.

Detection and discrimination of influenza B Victoria lineage deletion variant viruses by real-time RT-PCR.

BackgroundDuring the 2016/17 influenza season, influenza B/VIC lineage variant viruses emerged with two (K162N163) or three (K162N163D164) amino acid (aa) deletions in the haemagglutinin (HA) protein. There are currently five antigenically distinct HA proteins expressed by co-circulating influenza B viruses: B/YAM, B/VIC V1A (no deletion), B/VIC V1A-2DEL (2 aa deletion) and two antigenically distinguishable groups of B/VIC V1A-3DEL (3 aa deletion). The prevalence of these viruses differs across geographical regions, making it critical to have a sensitive, rapid diagnostic assay that detects and distinguishes these influenza B variant viruses during surveillance.AimOur objective was to develop a real-time RT-PCR (rRT-PCR) assay for detection and discrimination of influenza B/VIC lineage variant viruses.MethodsWe designed a diagnostic assay with one pair of conserved primers and three probes specific to each genetic group. We used propagated influenza B/VIC variant viruses and clinical specimens to assess assay performance.ResultsThis rRT-PCR assay detects and distinguishes the influenza B/VIC V1A, B/VIC V1A-2DEL, and B/VIC V1A-3DEL variant viruses, with no cross-reactivity. This assay can be run as a multiplex reaction, allowing for increased testing efficiency and reduced cost.ConclusionCoupling this assay with the Centers for Disease Control and Prevention's Human Influenza Virus Real-Time RT-PCR Diagnostic Panel Influenza B Lineage Genotyping Kit results in rapid detection and characterisation of circulating influenza B viruses. Detailed surveillance information on these distinct influenza B variant viruses will provide insight into their prevalence and geographical distribution and could aid in vaccine recommendations.

Genome-wide DNA methylation measurements in prostate tissues uncovers novel prostate cancer diagnostic biomarkers and transcription factor binding patterns.

BACKGROUND: Current diagnostic tools for prostate cancer lack specificity and sensitivity for detecting very early lesions. DNA methylation is a stable genomic modification that is detectable in peripheral patient fluids such as urine and blood plasma that could serve as a non-invasive diagnostic biomarker for prostate cancer. METHODS: We measured genome-wide DNA methylation patterns in 73 clinically annotated fresh-frozen prostate cancers and 63 benign-adjacent prostate tissues using the Illumina Infinium HumanMethylation450 BeadChip array. We overlaid the most significantly differentially methylated sites in the genome with transcription factor binding sites measured by the Encyclopedia of DNA Elements consortium. We used logistic regression and receiver operating characteristic curves to assess the performance of candidate diagnostic models. RESULTS: We identified methylation patterns that have a high predictive power for distinguishing malignant prostate tissue from benign-adjacent prostate tissue, and these methylation signatures were validated using data from The Cancer Genome Atlas Project. Furthermore, by overlaying ENCODE transcription factor binding data, we observed an enrichment of enhancer of zeste homolog 2 binding in gene regulatory regions with higher DNA methylation in malignant prostate tissues. CONCLUSIONS: DNA methylation patterns are greatly altered in prostate cancer tissue in comparison to benign-adjacent tissue. We have discovered patterns of DNA methylation marks that can distinguish prostate cancers with high specificity and sensitivity in multiple patient tissue cohorts, and we have identified transcription factors binding in these differentially methylated regions that may play important roles in prostate cancer development.

Genomic regulation of invasion by STAT3 in triple negative breast cancer.

Breast cancer is a heterogeneous disease comprised of four molecular subtypes defined by whether the tumor-originating cells are luminal or basal epithelial cells. Breast cancers arising from the luminal mammary duct often express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth receptor 2 (HER2). Tumors expressing ER and/or PR are treated with anti-hormonal therapies, while tumors overexpressing HER2 are targeted with monoclonal antibodies. Immunohistochemical detection of ER, PR, and HER2 receptors/proteins is a critical step in breast cancer diagnosis and guided treatment. Breast tumors that do not express these proteins are known as "triple negative breast cancer" (TNBC) and are typically basal-like. TNBCs are the most aggressive subtype, with the highest mortality rates and no targeted therapy, so there is a pressing need to identify important TNBC tumor regulators. The signal transducer and activator of transcription 3 (STAT3) transcription factor has been previously implicated as a constitutively active oncogene in TNBC. However, its direct regulatory gene targets and tumorigenic properties have not been well characterized. By integrating RNA-seq and ChIP-seq data from 2 TNBC tumors and 5 cell lines, we discovered novel gene signatures directly regulated by STAT3 that were enriched for processes involving inflammation, immunity, and invasion in TNBC. Functional analysis revealed that STAT3 has a key role regulating invasion and metastasis, a characteristic often associated with TNBC. Our findings suggest therapies targeting STAT3 may be important for preventing TNBC metastasis.

RNA sequencing of pancreatic adenocarcinoma tumors yields novel expression patterns associated with long-term survival and reveals a role for ANGPTL4.

BACKGROUND: Pancreatic adenocarcinoma patients have low survival rates due to late-stage diagnosis and high rates of cancer recurrence even after surgical resection. It is important to understand the molecular characteristics associated with survival differences in pancreatic adenocarcinoma tumors that may inform patient care. RESULTS: RNA sequencing was performed for 51 patient tumor tissues extracted from patients undergoing surgical resection, and expression was associated with overall survival time from diagnosis. Our analysis uncovered 323 transcripts whose expression correlates with survival time in our pancreatic patient cohort. This genomic signature was validated in an independent RNA-seq dataset of 68 additional patients from the International Cancer Genome Consortium. We demonstrate that this transcriptional profile is largely independent of markers of cellular division and present a 19-transcript predictive model built from a subset of the 323 transcripts that can distinguish patients with differing survival times across both the training and validation patient cohorts. We present evidence that a subset of the survival-associated transcripts is associated with resistance to gemcitabine treatment in vitro, and reveal that reduced expression of one of the survival-associated transcripts, Angiopoietin-like 4, impairs growth of a gemcitabine-resistant pancreatic cancer cell line. CONCLUSIONS: Gene expression patterns in pancreatic adenocarcinoma tumors can distinguish patients with differing survival outcomes after undergoing surgical resection, and the survival difference could be associated with the intrinsic gemcitabine sensitivity of primary patient tumors. Thus, these transcriptional differences may impact patient care by distinguishing patients who would benefit from a non-gemcitabine based therapy.

Blocking of targeted microRNAs from next-generation sequencing libraries.

Highly abundant microRNAs (miRNAs) in small RNA sequencing libraries make it difficult to obtain efficient measurements of more lowly expressed species. We present a new method that allows for the selective blocking of specific, abundant miRNAs during preparation of sequencing libraries. This technique is specific with little off-target effects and has no impact on the reproducibility of the measurement of non-targeted species. In human plasma samples, we demonstrate that blocking of highly abundant hsa-miR-16-5p leads to improved detection of lowly expressed miRNAs and more precise measurement of differential expression overall. Furthermore, we establish the ability to target a second abundant miRNA and to multiplex the blocking of two miRNAs simultaneously. For small RNA sequencing, this technique could fill a similar role as do ribosomal or globin removal technologies in messenger RNA sequencing.

Recurrent read-through fusion transcripts in breast cancer.

Read-through fusion transcripts that result from the splicing of two adjacent genes in the same coding orientation are a recently discovered type of chimeric RNA. We sought to determine if read-through fusion transcripts exist in breast cancer. We performed paired-end RNA-seq of 168 breast samples, including 28 breast cancer cell lines, 42 triple negative breast cancer primary tumors, 42 estrogen receptor positive (ER+) breast cancer primary tumors, and 56 non-malignant breast tissue samples. We analyzed the sequencing data to identify breast cancer associated read-through fusion transcripts. We discovered two recurrent read-through fusion transcripts that were identified in breast cancer cell lines, confirmed across breast cancer primary tumors, and were not detected in normal tissues (SCNN1A-TNFRSF1A and CTSD-IFITM10). Both fusion transcripts use canonical splice sites to join the last splice donor of the 5' gene to the first splice acceptor of the 3' gene, creating an in-frame fusion transcript. Western blots indicated that the fusion transcripts are translated into fusion proteins in breast cancer cells. Custom small interfering RNAs targeting the CTSD-IFITM10 fusion junction reduced expression of the fusion transcript and reduced breast cancer cell proliferation. Read-through fusion transcripts between adjacent genes with different biochemical functions represent a new type of recurrent molecular defect in breast cancer that warrant further investigation as potential biomarkers and therapeutic targets. Both breast cancer associated fusion transcripts identified in this study involve membrane proteins (SCNN1A-TNFRSF1A and CTSD-IFITM10), which raises the possibility that they could be breast cancer-specific cell surface markers.