Antigenicity of the Mu (B.1.621) and A.2.5 SARS-CoV-2 Spikes

The rapid emergence of SARS-CoV-2 variants is fueling the recent waves of the COVID-19 pandemic. Here, we assessed ACE2 binding and antigenicity of Mu (B.1.621) and A.2.5 Spikes. Both these variants carry some mutations shared by other emerging variants. Some of the pivotal mutations such as N501Y and E484K in the receptor-binding domain (RBD) detected in B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) are now present within the Mu variant. Similarly, the L452R mutation of B.1.617.2 (Delta) variant is present in A.2.5. In this study, we observed that these Spike variants bound better to the ACE2 receptor in a temperature-dependent manner. Pseudoviral particles bearing the Spike of Mu were similarly neutralized by plasma from vaccinated individuals than those carrying the Beta (B.1.351) and Delta (B.1.617.2) Spikes. Altogether, our results indicate the importance of measuring critical parameters such as ACE2 interaction, plasma recognition and neutralization ability of each emerging variant.

Rapid isolation and resolution immune evasion and viral fitness across contemporary SARS-CoV-2 variants

From late 2020 the world observed the rapid emergence of many distinct SARS-CoV-2 variants. At the same time, pandemic responses coalesced into significant global vaccine roll-out that have now significantly lowered Covid-19 hospital and mortality rates in the developed world. Over this period, we developed a rapid platform (R-20) for viral isolation and characterisation using primary remnant diagnostic swabs. This combined with quarantine testing and genomics surveillance, enabled the rapid isolation and characterisation of all major SARS-CoV-2 variants (all variants of concern and 6 variants of interest) globally with a 4-month period. This platform facilitated viral variant isolation and enabled rapid resolution of variant phenotype by allowing determining end point viral titers from primary nasopharyngeal swabs and through ranking of evasion of neutralising antibodies. In late 2021, when the Delta variant was dominating, Omicron rapidly emerged. Using this platform, we isolated and tested the first cases of this variant within Australia. In this setting we observed Omicron to diverge from other variants at two levels: Firstly, it ranks at the mots evasive to neutralisation antibodies compared to all VOCs and major VUIs. Secondly, it no longer engages TMPRSS2 during the late stages of fusion.

Containment of a multi-index B.1.1.7 outbreak on a university campus through a genomically-informed public health response

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.

Antibody binding and ACE2 binding inhibition is significantly reduced for the Omicron variant compared to all other variants of concern

The rapid emergence of the Omicron variant and its large number of mutations has led to its classification as a variant of concern (VOC) by the WHO. Initial studies on the neutralizing response towards this variant within convalescent and vaccinated individuals have identified substantial reductions. However many of these sample sets used in these studies were either small, uniform in nature, or were compared only to wild-type (WT) or, at most, a few other VOC. Here, we assessed IgG binding, (Angiotensin-Converting Enzyme 2) ACE2 binding inhibition, and antibody binding dynamics for the omicron variant compared to all other VOC and variants of interest (VOI), in a large cohort of infected, vaccinated, and infected and then vaccinated individuals. While omicron was capable of binding to ACE2 efficiently, antibodies elicited by infection or immunization showed reduced IgG binding and ACE2 binding inhibition compared to WT and all VOC. Among vaccinated samples, antibody binding responses towards omicron were only improved following administration of a third dose. Overall, our results identify that omicron can still bind ACE2 while pre-existing antibodies can bind omicron. The extent of the mutations appear to inhibit the development of a neutralizing response, and as a result, omicron remains capable of evading immune control.

Rapid selection of P323L in the SARS-CoV-2 polymerase (NSP12) in humans and non-human primate models and confers a large plaque phenotype

The mutational landscape of SARS-CoV-2 varies at both the dominant viral genome sequence and minor genomic variant population. An early change associated with transmissibility was the D614G substitution in the spike protein. This appeared to be accompanied by a P323L substitution in the viral polymerase (NSP12), but this latter change was not under strong selective pressure. Investigation of P323L/D614G changes in the human population showed rapid emergence during the containment phase and early surge phase of wave 1 in the UK. This rapid substitution was from minor genomic variants to become part of the dominant viral genome sequence. A rapid emergence of 323L but not 614G was observed in a non-human primate model of COVID-19 using a starting virus with P323 and D614 in the dominant genome sequence and 323L and 614G in the minor variant population. In cell culture, a recombinant virus with 323L in NSP12 had a larger plaque size than the same recombinant virus with P323. These data suggest that it may be possible to predict the emergence of a new variant based on tracking the distribution and frequency of minor variant genomes at a population level, rather than just focusing on providing information on the dominant viral genome sequence e.g., consensus level reporting. The ability to predict an emerging variant of SARS-CoV-2 in the global landscape may aid in the evaluation of medical countermeasures and non-pharmaceutical interventions.

Biofunctionalized nano-antimicrobials - progress, prospects and challenges

The rapid emergence of multidrug resistant bacterial strains clearly highlights the need for the development of new antimicrobial compounds/materials to address associated healthcare challenges. Meanwhile, the adverse side effects of conventional antibiotics on human health urge the development of new natural product-based antimicrobials to minimize the side effects. In this respect, we concisely review the recent scientific contributions to develop natural product-based nano-antibiotics. The focus of the review is on the use of flavonoids, peptides, and cationic biopolymer functionalized metal/metal oxide nanoparticles as efficient tools to hit the MDR bacterial strains. It summarizes the most recent aspects of the functionalized nanoparticles against various pathogenic bacterial strains with respect to their minimal inhibitory concentrations and mechanism of action at the cellular and molecular levels. At the end, the future perspectives to materialize the in vivo applications of nano-antimicrobials are suggested on the basis of the available research.

Household serial interval of COVID-19 and the effect of Variant B.1.1.7: analyses from prospective community cohort study (Virus Watch)

Introduction: Increased transmissibility of B.1.1.7 variant of concern (VOC) in the UK may explain its rapid emergence and global spread. We analysed data from putative household infector - infectee pairs in the Virus Watch Community cohort study to assess the serial interval of COVID-19 and whether this was affected by emergence of the B.1.1.7 variant. Methods: The Virus Watch study is an online, prospective, community cohort study following up entire households in England and Wales during the COVID-19 pandemic. Putative household infector-infectee pairs were identified where more than one person in the household had a positive swab matched to an illness episode. Data on whether or not individual infections were caused by the B.1.1.7 variant were not available. We therefore developed a classification system based on the percentage of cases estimated to be due to B.1.1.7 in national surveillance data for different English regions and study weeks. Results: Out of 24,887 illnesses reported, 915 tested positive for SARS-CoV-2 and 186 likely ‘infector-infectee’ pairs in 186 households amongst 372 individuals were identified. The mean COVID-19 serial interval was 3.18 (95%CI: 2.55-3.81, sd=4.36) days. There was no significant difference (p=0.267) between the mean serial interval for VOC hotspots (mean = 3.64 days, (95%CI: 2.55 – 4.73)) days and non-VOC hotspots, (mean = 2.72 days, (95%CI: 1.48 – 3.96)). Conclusions: Our estimates of the average serial interval of COVID-19 are broadly similar to estimates from previous studies and we find no evidence that B.1.1.7 is associated with a change in serial intervals. Alternative explanations such as increased viral load, longer period of viral shedding or improved receptor binding may instead explain the increased transmissibility and rapid spread and should undergo further investigation.

SARS-CoV-2 Omicron: reduction of potent humoral responses and resistance to clinical immunotherapeutics relative to viral variants of concern

From late 2020 the world observed the rapid emergence of many distinct SARS-CoV-2 variants. At the same time, pandemic responses resulted in significant global vaccine rollouts that have now significantly lowered Covid-19 hospitalisation and mortality rates in the developed world. Unfortunately, in late 2021, the variant Omicron (B.1.1.529) emerged and it eclipsed the other variants of concern (VOC) in its number of Spike polymorphisms, and its ability to compete with and displacement of the dominant VOC Delta. Herein we accessed the impact of Omicron to humoral neutralisation in vaccinated, convalescent cohorts, in concentrated human IgG from thousands of plasma donors and also alongside many clinically used monoclonal antibodies. Overall, we observed a 17 to 22 fold drop in neutralisation titres across all donors that reached a titre to Omicron. Concentrated pooled human IgG from convalescent and vaccinated donors had greater breadth but was still reduced by 16-fold. In all therapeutic antibodies tested, significant neutralization was only observed for Sotrovimab, with other monoclonals unable to neutralize B.1.1.529.

Suppressing Alpha-Hemolysin as Potential Target to Screen of Flavonoids to Combat Bacterial Coinfection

The rapid emergence of bacterial coinfection caused by cytosolic bacteria has become a huge threat to public health worldwide. Past efforts have been devoted to discover the broad-spectrum antibiotics, while the emergence of antibiotic resistance encourages the development of antibacterial agents. In essence, bacterial virulence is a factor in antibiotic tolerance. However, the discovery and development of new antibacterial drugs and special antitoxin drugs is much more difficult in the antibiotic resistance era. Herein, we hypothesize that antitoxin hemolytic activity can serve as a screening principle to select antibacterial drugs to combat coinfection from natural products. Being the most abundant natural drug of plant origins, flavonoids were selected to assess the ability of antibacterial coinfections in this paper. Firstly, we note that four flavonoids, namely, baicalin, catechin, kaempferol, and quercetin, have previously exhibited antibacterial abilities. Then, we found that baicalin, kaempferol, and quercetin have better inhibitions of hemolytic activity of Hla than catechin. In addition, kaempferol and quercetin, have therapeutic effectivity for the coinfections of Staphylococcus aureus and Pseudomonas aeruginosa in vitro and in vivo. Finally, our results indicated that kaempferol and quercetin therapied the bacterial coinfection by inhibiting S. aureus α-hemolysin (Hla) and reduced the host inflammatory response. These results suggest that antitoxins may play a promising role as a potential target for screening flavonoids to combat bacterial coinfection.

AI Startup Business Models

We currently observe the rapid emergence of startups that use Artificial Intelligence (AI) as part of their business model. While recent research suggests that AI startups employ novel or different business models, one could argue that AI technology has been used in business models for a long time already—questioning the novelty of those business models. Therefore, this study investigates how AI startup business models potentially differ from common IT-related business models. First, a business model taxonomy of AI startups is developed from a sample of 100 AI startups and four archetypal business model patterns are derived: AI-charged Product/Service Provider, AI Development Facilitator, Data Analytics Provider, and Deep Tech Researcher. Second, drawing on this descriptive analysis, three distinctive aspects of AI startup business models are discussed: (1) new value propositions through AI capabilities, (2) different roles of data for value creation, and (3) the impact of AI technology on the overall business logic. This study contributes to our fundamental understanding of AI startup business models by identifying their key characteristics, common instantiations, and distinctive aspects. Furthermore, this study proposes promising directions for future entrepreneurship research. For practice, the taxonomy and patterns serve as structured tools to support entrepreneurial action.