Search

BackgroundHospital-acquired influenza virus infection (HAII) can cause severe morbidity and mortality. Identifying potential transmission routes can inform prevention strategies.MethodsWe identified all hospitalized patients testing positive for influenza A virus at a large, tertiary care hospital during the 2017–2018 and 2019–2020 influenza seasons. Hospital admission dates, locations of inpatient service, and clinical influenza testing information were retrieved from the electronic medical record. Time-location groups of epidemiologically linked influenza patients were defined and contained ≥1 presumed HAII case (first positive ≥48 hours after admission). Genetic relatedness within time-location groups was assessed by whole genome sequencing.ResultsDuring the 2017–2018 season, 230 patients tested positive for influenza A(H3N2) or unsubtyped influenza A including 26 HAIIs. There were 159 influenza A(H1N1)pdm09 or unsubtyped influenza A–positive patients identified during the 2019–2020 season including 33 HAIIs. Consensus sequences were obtained for 177 (77%) and 57 (36%) of influenza A cases in 2017–2018 and 2019–2020, respectively. Among all influenza A cases, there were 10 time-location groups identified in 2017–2018 and 13 in 2019–2020; 19 of 23 groups included ≤4 patients. In 2017–2018, 6 of 10 groups had ≥2 patients with sequence data, including ≥1 HAII case. Two of 13 groups met this criteria in 2019–2020. Two time-location groups from 2017–2018 each contained 3 genetically linked cases.ConclusionsOur results suggest that HAIIs arise from outbreak transmission from nosocomial sources as well as single infections from unique community introductions.

The first cluster of SARS-CoV-2 cases with lineage B.1.1.7 in the state of Michigan was identified through intensive university-led surveillance sampling and targeted sequencing. A collaborative investigation and response was conducted by the local and state health departments, and the campus and athletic medicine COVID-19 response teams, using S-gene target failure screening and rapid genomic sequencing to inform containment strategies. A total of 50 cases of B.1.1.7-lineage SARS-CoV-2 were identified in this outbreak, which was due to three coincident introductions of B.1.1.7-lineage SARS-CoV-2, all of which were genetically distinct from lineages which later circulated in the broader community. This investigation demonstrates the successful implementation of a genomically-informed outbreak response which can be extended to university campuses and other settings at high risk for rapid emergence of new variants.

Background Coronavirus disease 2019 (COVID-19) has had high incidence rates at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are poorly understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities. Methods We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan and the surrounding community during the Fall 2020 semester (August 16–November 24). We sequenced complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from 1659 individuals, including 468 students, representing 20% of cases in students and 25% of total cases in Washtenaw County over the study interval. Results Phylogenetic analysis identified >200 introductions into the student population, most of which were not related to other student cases. There were 2 prolonged student transmission clusters, of 115 and 73 individuals, that spanned multiple on-campus residences. Remarkably, Conclusions The largest outbreaks among students at the University of Michigan did not significantly contribute to the rise in community cases in Fall 2020. These results provide valuable insights into SARS-CoV-2 transmission dynamics at the regional level.

COVID-19 has had high incidence at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are not well understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities. We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan-Ann Arbor and the surrounding community during the Fall 2020 semester (August 16th –November 24th). We sequenced complete SARS-CoV-2 genomes from 1659 individuals, including 468 students, representing 20% of cases in students and 25% of total confirmed cases in Washtenaw County over the study interval. Phylogenetic analysis identified over 200 introductions into the student population, most of which were not related to other student cases. There were two prolonged transmission clusters among students that spanned across multiple on-campus residences. However, there were very few genetic descendants of student clusters among non-students during a subsequent November wave of infections in the community. We conclude that outbreaks at the University of Michigan did not significantly contribute to the rise in Washtenaw County COVID-19 incidence during November 2020. These results provide valuable insights into the distinct transmission dynamics of SARS-CoV-2 among IHE populations and surrounding communities.

Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified viral load as a critical factor in variant identification. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology., Author summary Understanding the evolution and transmission of SARS-CoV-2 is important for designing public health interventions to prevent outbreaks. Viral genome sequencing has been widely used to reconstruct patterns of SARS-CoV-2 transmission through communities and to monitor the spread of new strains. However, because SARS-CoV-2 can transmit multiple times before a new mutation fixes, consensus sequences often cannot determine “who infected whom.” Identifying individuals who share the same viral genetic variants at low frequencies within each infection may help resolve this problem, but to do this we need to accurately identify within-host genetic variants and understand how they evolve and spread. We investigated within-host diversity of SARS-CoV-2 with samples collected in southeastern Michigan in March–May 2020. We show that there are relatively few genetic variants present in any given infection, and variants do not tend to accumulate in people over time. We also found that people who are not part of the same epidemic cluster can share the same within-host variants, due to chance or various evolutionary forces.

We describe a case of proven transmission of SARS-CoV-2 from lung donor to recipient. The donor had no clinical history or findings suggestive of infection with SARS-CoV-2 and tested negative by reverse transcriptase polymerase chain reaction (RT-PCR) on a nasopharyngeal (NP) swab obtained within 48 h of procurement. Lower respiratory tract testing was not performed. The recipient developed fever, hypotension, and pulmonary infiltrates on posttransplant day (PTD) 3, and RT-PCR testing for SARS-CoV-2 on an NP swab specimen was non-reactive, but positive on bronchoalveolar lavage (BAL) fluid. One thoracic surgeon present during the transplantation procedure developed COVID-19. Sequence analysis of isolates from donor BAL fluid (obtained at procurement), the recipient, and the infected thoracic surgeon proved donor origin of recipient and health-care worker (HCW) infection. No other organs were procured from this donor. Transplant centers and organ procurement organizations should perform SARS-CoV-2 testing of lower respiratory tract specimens from potential lung donors, and consider enhanced personal protective equipment for HCWs involved in lung procurement and transplantation.

Background Previous studies demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be detected for weeks after infection. The significance of this finding is unclear and, in most patients, does not represent active infection. Detection of subgenomic RNA has been proposed to represent productive infection and may be a useful marker for monitoring infectivity. Methods We used quantitative reverse-transcription polymerase chain reaction (RT-qPCR) to quantify total and subgenomic nucleocapsid (sgN) and envelope (sgE) transcripts in 185 SARS-CoV-2–positive nasopharyngeal swab samples collected on hospital admission and to relate to symptom duration. Results We find that all transcripts decline at the same rate; however, sgE becomes undetectable before other transcripts. The median duration of symptoms to a negative test is 14 days for sgE and 25 days for sgN. There is a linear decline in subgenomic compared to total RNA, suggesting that subgenomic transcript copy number is dependent on copy number of total transcripts. The mean difference between total and sgN is 16-fold and the mean difference between total and sgE is 137-fold. This relationship is constant over duration of symptoms, allowing prediction of subgenomic copy number from total copy number. Conclusions Subgenomic RNA may be no more useful in determining infectivity than a copy number threshold determined for total RNA.

SummaryThe emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

We describe a case of chronic COVID-19 in a patient with lymphoma and associated B-cell immunodeficiency. Viral cultures and sequence analysis demonstrate ongoing replication of infectious SARS-CoV-2 virus for at least 119 days. The patient had three admissions related to COVID-19 over a four-month period and was treated twice with remdesivir and convalescent plasma with resolution of symptoms. The patient’s lack of seroconversion and prolonged course illustrate the importance of humoral immunity in resolving SARS-CoV-2 infection. This case highlights challenges in managing immunocompromised hosts, who may act as persistent shedders and sources of transmission.

Mitochondrial trafficking plays a central role in dorsal root ganglion (DRG) neuronal cell survival and neurotransmission by transporting mitochondria from the neuronal cell body throughout the bundles of DRG axons. In type 2 diabetes (T2DM), dyslipidemia and hyperglycemia damage DRG neurons and induce mitochondrial dysfunction; however, the impact of free fatty acids and glucose on mitochondrial trafficking in DRG neurons remains unknown. To evaluate the impact of free fatty acids compared to hyperglycemia on mitochondrial transport, primary adult mouse DRG neuron cultures were treated with physiologic concentrations of palmitate and glucose and assessed for alterations in mitochondrial trafficking, mitochondrial membrane potential, and mitochondrial bioenergetics. Palmitate treatment significantly reduced the number of motile mitochondria in DRG axons, but physiologic concentrations of glucose did not impair mitochondrial trafficking dynamics. Palmitate-treated DRG neurons also exhibited a reduction in mitochondrial velocity, and impaired mitochondrial trafficking correlated with mitochondrial depolarization in palmitate-treated DRG neurons. Finally, we found differential bioenergetic effects of palmitate and glucose on resting and energetically challenged mitochondria in DRG neurons. Together, these results suggest that palmitate induces DRG neuron mitochondrial depolarization, inhibiting axonal mitochondrial trafficking and altering mitochondrial bioenergetic capacity.—Rumora, A. E., Lentz, S. I., Hinder, L. M., Jackson, S. W., Valesano, A., Levinson, G. E., Feldman, E. L. Dyslipidemia impairs mitochondrial trafficking and function in sensory neurons.

Influenza B virus undergoes seasonal antigenic drift more slowly than influenza A, but the reasons for this difference are unclear. While the evolutionary dynamics of influenza viruses play out globally, they are fundamentally driven by mutation, reassortment, drift, and selection within individual hosts. These processes have recently been described for influenza A virus, but little is known about the evolutionary dynamics of influenza B virus (IBV) at the level of individual infections and transmission events. Here we define the within-host evolutionary dynamics of influenza B virus by sequencing virus populations from naturally-infected individuals enrolled in a prospective, community-based cohort over 8176 person-seasons of observation. Through analysis of high depth-of-coverage sequencing data from samples from 91 individuals with influenza B, we find that influenza B virus accumulates lower genetic diversity than previously observed for influenza A virus during acute infections. Consistent with studies of influenza A viruses, the within-host evolution of influenza B viruses is characterized by purifying selection and the general absence of widespread positive selection of within-host variants. Analysis of shared genetic diversity across 15 sequence-validated transmission pairs suggests that IBV experiences a tight transmission bottleneck similar to that of influenza A virus. These patterns of local-scale evolution are consistent with influenza B virus’ slower global evolutionary rate.ImportanceThe evolution of influenza virus is a significant public health problem and necessitates the annual evaluation of influenza vaccine formulation to keep pace with viral escape from herd immunity. Influenza B virus is a serious health concern for children, in particular, yet remains understudied compared to influenza A virus. Influenza B virus evolves more slowly than influenza A, but the factors underlying this are not completely understood. We studied how the within-host diversity of influenza B virus relates to its global evolution by sequencing viruses from a community-based cohort. We found that influenza B virus populations have lower within-host genetic diversity than influenza A virus and experience a tight genetic bottleneck during transmission. Our work provides insights into the varying dynamics of influenza viruses in human infection.

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight that the primary ports of entry for B.1.1.7 in the US were in New York, California, and Florida. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response., The SARS-CoV-2 variant B.1.1.7 was introduced to the United States in early December 2020 and soon became established within many communities. The primary points of entry into the US are identified as NY, CA, and FL, and exponential growth in these states resulted in spread to neighboring states.

Summary The emergence of circulating vaccine-derived polioviruses through evolution of the oral polio vaccine (OPV) poses a significant obstacle to polio eradication. Understanding the early genetic changes that occur as OPV evolves and transmits is important for preventing future outbreaks. Here, we use deep sequencing to define the evolutionary trajectories of type 2 OPV in a vaccine trial. By sequencing 497 longitudinal stool samples from 271 OPV2 recipients and household contacts, we were able to examine the extent of convergent evolution in vaccinated individuals and the amount of viral diversity that is transmitted. In addition to rapid reversion of key attenuating mutations, we identify strong selection at 19 sites across the genome. We find that a tight transmission bottleneck limits the onward transmission of these early adaptive mutations. Our results highlight the distinct evolutionary dynamics of live attenuated virus vaccines and have important implications for the success of next-generation OPV., Graphical Abstract, Highlights • We used deep sequencing to define the evolutionary trajectories of type 2 OPV • We identified strong positive selection at multiple, non-attenuating sites • Transmission bottleneck limits spread of variants that are selected within hosts • This work provides insights into the evolution of live attenuated virus vaccines, The emergence of vaccine-derived polioviruses through evolution of the oral polio vaccine poses a significant obstacle to global poliovirus eradication. Valesano et al. use sequencing of samples from vaccine recipients and household contacts to identify multiple mutations that are selected within hosts. Tight bottlenecks limit the onward transmission of these variants.