45 research outputs found
Enhancing rAAV production by HEK293 cells via metabolic profiling
Viral vector manufacturing is expensive and time-consuming. Demand for rAAV-based vectors has risen
massively in the past decade and continues to rise thanks to urgent healthcare supply demand. The industry is,
however, currently missing a cost-effective and robust manufacturing strategy. One of the major downsides of
rAAV production is the high percentage of “empty” vector particles being produced and harvested. In addition to
complicating downstream purification processes, this characteristic limits the efficiency of rAAV manufacture
and presents uncertainties for scale-up.
Efficiency of the manufacturing process is largely dependent on the productivity of the production cell line. Much
emphasis has been put into understanding the effects of recombinant protein production on mammalian cell
lines (e.g., CHO, HeLa, HEK293) but relatively little is known about the effects of viral vector production on cell
biology and behaviour. Over the years, many clones have been derived, isolated and engineered from HEK293
to induce improvements in productivity and efficiency. However, the high cost of production and licensing, the
expression of potentially undesired elements (e.g., T-antigen) and regulatory approval processes for next
generation cell lines, hinders their use in clinical manufacturing. Increased understanding of HEK293 in relation
to existing processes and process control offers realistic opportunity to enhance the efficiency of rAAV
manufacturing.
Our aim is to identify and understand the critical parameters that contribute to setting the productivity in HEK293
cells (in terms of final yield and abundance of full capsids), ranging from the metabolic requirements prior to and
during viral vector production, to cell culture parameter optimisation to maintain the cells in an optimal state of
health.
We tested several commercially available media for rAAV9 production and selected the candidate that provided
the best yield and quality of viral vector. With this medium as our baseline, we investigated the metabolism
during a period of culture via extracellular metabolic profiling of control and rAAV producing cells. The analysis
revealed the rapid use of several amino acids over the first 24 hr post-inoculation and the subsequent
generation of metabolites indicative of metabolic profiles associated with cell growth. rAAV9 producing cells
show lower rates of amino acid and glucose consumption than control cells but the profile of metabolism was
not significantly changed as a result of transfection/production of rAAV9. These data were used to design
medium supplements and the effect of supplement addition on cell proliferation, viability and rAAV
production/quality was assessed. Specific combinations of amino acids generated an increased cell density (up
to 9.3x106 cells/mL at 5 days post-inoculation compared to 4.4x106 cells/mL for cells in non-supplemented
medium). This was associated with retention of improved viability in the presence of the supplement. In addition,
the metabolic profiling we undertook indicated the build-up of potentially toxic/growth inhibitory metabolites
during the period of stock cell preparations prior to setting up transfections. In various dilution experiments we
were able to optimise the pre-treatment, cell density and dilution protocol to generate predictable and
reproducible efficiencies of transfection, cell growth and rAAV production.
Overall, our data contributes metabolic insights to process conditions that generate HEK293 cells of appropriate
health and defined parameters to robust and enhanced production of rAAV, providing work schemes that are
also appropriate to the manufacture of further types of viral vectors
High-resolution characterisation of short-term temporal variability in the taxonomic and resistome composition of wastewater influent
Wastewater-based epidemiology (WBE) for population-level surveillance of antimicrobial resistance (AMR) is gaining significant traction, but the impact of wastewater sampling methods on results is unclear. In this study, we characterized taxonomic and resistome
differences between single-timepoint-grab and 24 h composites of wastewater influent from a large UK-based wastewater treatment
work [WWTW (population equivalent: 223435)]. We autosampled hourly influent grab samples (n=72) over three consecutive weekdays, and prepared additional 24 h composites (n=3) from respective grabs. For taxonomic profiling, metagenomic DNA was extracted
from all samples and 16S rRNA gene sequencing was performed. One composite and six grabs from day 1 underwent metagenomic
sequencing for metagenomic dissimilarity estimation and resistome profiling. Taxonomic abundances of phyla varied significantly
across hourly grab samples but followed a repeating diurnal pattern for all 3days. Hierarchical clustering grouped grab samples into
four time periods dissimilar in both 16S rRNA gene-based profiles and metagenomic distances. 24H-composites resembled mean
daily phyla abundances and showed low variability of taxonomic profiles. Of the 122 AMR gene families (AGFs) identified across all
day 1 samples, single grab samples identified a median of six (IQR: 5–8) AGFs not seen in the composite. However, 36/36 of these hits
were at lateral coverage <0.5 (median: 0.19; interquartile range: 0.16–0.22) and potential false positives. Conversely, the 24H-composite
identified three AGFs not seen in any grab with higher lateral coverage (0.82; 0.55–0.84). Additionally, several clinically significant human
AGFs (blaVIM, blaIMP, blaKPC) were intermittently or completely missed by grab sampling but captured by the 24 h composite. Wastewater
influent undergoes significant taxonomic and resistome changes on short timescales potentially affecting interpretation of results
based on sampling strategy. Grab samples are more convenient and potentially capture low-prevalence/transient targets but are less
comprehensive and temporally variable. Therefore, we recommend 24H-composite sampling where feasible. Further validation and
optimization of WBE methods is vital for its development into a robust AMR surveillance approach
High-resolution characterization of short-term temporal variability in the taxonomic and resistome composition of wastewater influent
Wastewater-based epidemiology (WBE) for population-level surveillance of antimicrobial resistance (AMR) is gaining significant traction, but the impact of wastewater sampling methods on results is unclear. In this study, we characterized taxonomic and resistome differences between single-timepoint-grab and 24 h composites of wastewater influent from a large UK-based wastewater treatment work [WWTW (population equivalent: 223 435)]. We autosampled hourly influent grab samples (n=72) over three consecutive weekdays, and prepared additional 24 h composites (n=3) from respective grabs. For taxonomic profiling, metagenomic DNA was extracted from all samples and 16S rRNA gene sequencing was performed. One composite and six grabs from day 1 underwent metagenomic sequencing for metagenomic dissimilarity estimation and resistome profiling. Taxonomic abundances of phyla varied significantly across hourly grab samples but followed a repeating diurnal pattern for all 3 days. Hierarchical clustering grouped grab samples into four time periods dissimilar in both 16S rRNA gene-based profiles and metagenomic distances. 24H-composites resembled mean daily phyla abundances and showed low variability of taxonomic profiles. Of the 122 AMR gene families (AGFs) identified across all day 1 samples, single grab samples identified a median of six (IQR: 5–8) AGFs not seen in the composite. However, 36/36 of these hits were at lateral coverage <0.5 (median: 0.19; interquartile range: 0.16–0.22) and potential false positives. Conversely, the 24H-composite identified three AGFs not seen in any grab with higher lateral coverage (0.82; 0.55–0.84). Additionally, several clinically significant human AGFs (bla VIM, bla IMP, bla KPC) were intermittently or completely missed by grab sampling but captured by the 24 h composite. Wastewater influent undergoes significant taxonomic and resistome changes on short timescales potentially affecting interpretation of results based on sampling strategy. Grab samples are more convenient and potentially capture low-prevalence/transient targets but are less comprehensive and temporally variable. Therefore, we recommend 24H-composite sampling where feasible. Further validation and optimization of WBE methods is vital for its development into a robust AMR surveillance approach
Towards Developer-Centered Automatic Program Repair:Findings from Bloomberg
This paper reports on qualitative research into automatic program repair (APR) at Bloomberg. Six focus groups were conducted with a total of seventeen participants (including both developers of the APR tool and developers using the tool) to consider: the development at Bloomberg of a prototype APR tool (Fixie); developers' early experiences using the tool; and developers' perspectives on how they would like to interact with the tool in future. APR is developing rapidly and it is important to understand in greater detail developers' experiences using this emerging technology. In this paper, we provide in-depth, qualitative data from an industrial setting. We found that the development of APR at Bloomberg had become increasingly user-centered, emphasising how fixes were presented to developers, as well as particular features, such as cus-tomisability. From the focus groups with developers who had used Fixie, we found particular concern with the pragmatic aspects of APR, such as how and when fixes were presented to them. Based on our findings, we make a series of recommendations to inform future APR development, highlighting how APR tools should 'start small', be customisable, and fit with developers' workflows. We also suggest that APR tools should capitalise on the promise of repair bots and draw on advances in explainable AI
Towards Developer-Centered Automatic Program Repair: Findings from Bloomberg
This paper reports on qualitative research into automatic program repair (APR) at Bloomberg. Six focus groups were conducted with a total of seventeen participants (including both developers of the APR tool and developers using the tool) to consider: the development at Bloomberg of a prototype APR tool (Fixie); developers' early experiences using the tool; and developers' perspectives on how they would like to interact with the tool in future. APR is developing rapidly and it is important to understand in greater detail developers' experiences using this emerging technology. In this paper, we provide in-depth, qualitative data from an industrial setting. We found that the development of APR at Bloomberg had become increasingly user-centered, emphasising how fixes were presented to developers, as well as particular features, such as cus-tomisability. From the focus groups with developers who had used Fixie, we found particular concern with the pragmatic aspects of APR, such as how and when fixes were presented to them. Based on our findings, we make a series of recommendations to inform future APR development, highlighting how APR tools should 'start small', be customisable, and fit with developers' workflows. We also suggest that APR tools should capitalise on the promise of repair bots and draw on advances in explainable AI.Output Status: Forthcomin
Towards Developer-Centered Automatic Program Repair: Findings from Bloomberg
This paper reports on qualitative research into automatic program repair (APR) at Bloomberg. Six focus groups were conducted with a total of seventeen participants (including both developers of the APR tool and developers using the tool) to consider: the development at Bloomberg of a prototype APR tool (Fixie); developers' early experiences using the tool; and developers' perspectives on how they would like to interact with the tool in future. APR is developing rapidly and it is important to understand in greater detail developers' experiences using this emerging technology. In this paper, we provide in-depth, qualitative data from an industrial setting. We found that the development of APR at Bloomberg had become increasingly user-centered, emphasising how fixes were presented to developers, as well as particular features, such as cus-tomisability. From the focus groups with developers who had used Fixie, we found particular concern with the pragmatic aspects of APR, such as how and when fixes were presented to them. Based on our findings, we make a series of recommendations to inform future APR development, highlighting how APR tools should 'start small', be customisable, and fit with developers' workflows. We also suggest that APR tools should capitalise on the promise of repair bots and draw on advances in explainable AI
High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with \u3e90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were “novel” SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases
Water velocity limits the temporal extent of herbivore effects on aquatic plants in a lowland river
The role of herbivores in regulating aquatic plant dynamics has received growing recognition from researchers and managers. However, the evidence for herbivore impacts on aquatic plants is largely based on short-term exclosure studies conducted within a single plant growing season. Thus, it is unclear how long herbivore impacts on aquatic plant abundance can persist for. We addressed this knowledge gap by testing whether mute swan (Cygnus olor) grazing on lowland river macrophytes could be detected in the following growing season. Furthermore, we investigated the role of seasonal changes in water current speed in limiting the temporal extent of grazing. We found no relationship between swan biomass density in 1 year and aquatic plant cover or biomass in the following spring. No such carry-over effects were detected despite observing high swan biomass densities in the previous year from which we inferred grazing impacts on macrophytes. Seasonal increases in water velocity were associated with reduced grazing pressure as swans abandoned river habitat. Furthermore, our study highlights the role of seasonal changes in water velocity in determining the length of the mute swan grazing season in shallow lowland rivers and thus in limiting the temporal extent of herbivore impacts on aquatic plant abundance
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Niche and local geography shape the pangenome of wastewater- and livestock-associated Enterobacteriaceae
Escherichia coli and other Enterobacteriaceae are diverse species with “open” pangenomes, where genes move intra- and interspecies via horizontal gene transfer. However, most analyses focus on clinical isolates. The pangenome dynamics of natural populations remain understudied, despite their suggested role as reservoirs for antimicrobial resistance (AMR) genes. Here, we analyze near-complete genomes for 827 Enterobacteriaceae (553 Escherichia and 274 non-Escherichia spp.) with 2292 circularized plasmids in total, collected from 19 locations (livestock farms and wastewater treatment works in the United Kingdom) within a 30-km radius at three time points over a year. We find different dynamics for chromosomal and plasmid-borne genes. Plasmids have a higher burden of AMR genes and insertion sequences, and AMR-gene-carrying plasmids show evidence of being under stronger selective pressure. Environmental niche and local geography both play a role in shaping plasmid dynamics. Our results highlight the importance of local strategies for controlling the spread of AMR
Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial
SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication