Nabin K. Shrestha, Patrick C. Burke, Amy S. Nowacki, Paul Terpeluk, Steven M. Gordon

Background: There are good reasons to expect natural infection to provide protection against future infection with SARS-CoV-2. The purpose of this study was to evaluate the necessity of COVID-19 vaccination in persons previously infected with SARS-CoV-2. Methods: Employees of the Cleveland Clinic Health System working in Ohio on Dec 16, 2020, the day COVID-19 vaccination was started, were included. Any subject who tested positive for SARS-CoV-2 at least 42 days earlier was considered previously infected. One was considered vaccinated 14 days after receipt of the second dose of a SARS-CoV-2 mRNA vaccine. The cumulative incidence of SARS-CoV-2 infection over the next four months, among previously infected subjects who received the vaccine, was compared with those of previously infected subjects who remained unvaccinated, previously uninfected subjects who received the vaccine, and previously uninfected subjects who remained unvaccinated. Results: Among the 52238 included employees, 1220 (47%) of 2579 previously infected subjects received the vaccine, compared with 29461 (59%) of 49659 not previously infected. The cumulative incidence of SARS-CoV-2 infection did not differ among previously infected unvaccinated subjects, previously infected subjects who were vaccinated, and previously uninfected subjects who were vaccinated, and was much lower than that of previously uninfected subjects who remained unvaccinated. Not one of the 1359 previously infected subjects who remained unvaccinated had a SARS-CoV-2 infection over the duration of the study. Conclusion: Individuals who have had SARS-CoV-2 infection are unlikely to benefit from COVID-19 vaccination, and vaccines can be safely prioritized to those who have not been infected before.

F. Konstantin Föhse, Büsranur Geckin, Gijs J. Overheul, Josephine van de Maat, Gizem Kilic, Ozlem Bulut, Helga Dijkstra, Heidi Lemmers, S. Andrei Sarlea, Maartje Reijnders, Jacobien Hoogerwerf, Jaap ten Oever, Elles Simonetti, Frank L van de Veerdonk, Leo A.B. Joosten, Bart L. Haagmans, Reinout van Crevel, Yang Li, Ronald P. van Rij, Corine GeurtsvanKessel, Marien I. de Jonge, Jorge Domínguez-Andrés, Mihai G. Netea

The mRNA-based BNT162b2 vaccine from Pfizer/BioNTech was the first registered COVID-19 vaccine and has been shown to be up to 95% effective in preventing SARS-CoV-2 infections. Little is known about the broad effects of the new class of mRNA vaccines, especially whether they have combined effects on innate and adaptive immune responses. Here we confirmed that BNT162b2 vaccination of healthy individuals induced effective humoral and cellular immunity against several SARS-CoV-2 variants. Interestingly, however, the BNT162b2 vaccine also modulated the production of inflammatory cytokines by innate immune cells upon stimulation with both specific (SARS-CoV-2) and non-specific (viral, fungal and bacterial) stimuli. The response of innate immune cells to TLR4 and TLR7/8 ligands was lower after BNT162b2 vaccination, while fungi-induced cytokine responses were stronger. In conclusion, the mRNA BNT162b2 vaccine induces complex functional reprogramming of innate immune responses, which should be considered in the development and use of this new class of vaccines.

Qing Yang, Tassa Saldi, Erika Lasda, Carolyn J. Decker, Camille L. Paige, Denise Muhlrad, Patrick Gonzalez, Morgan R. Fink, Kimngan L. Tat, Cole R. Hager, Jack C. Davis, Christopher D Ozeroff, Nicholas R. Meyerson, Stephen K. Clark, Will T. Fattor, Alison R. Gilchrist, Arturo Barbachano-Guerrero, Emma R. Worden-Sapper, Sharon S. Wu, Gloria R. Brisson, Matthew B McQueen, Robin D Dowell, Leslie A Leinwand, Roy Parker, Sara L Sawyer

We analyze data from the Fall 2020 pandemic response efforts at the University of Colorado Boulder (USA), where more than 72,500 saliva samples were tested for SARS-CoV-2 using quantitative RT-PCR. All samples were collected from individuals who reported no symptoms associated with COVID-19 on the day of collection. From these, 1,405 positive cases were identified. The distribution of viral loads within these asymptomatic individuals was indistinguishable from what has been previously reported in symptomatic individuals. Regardless of symptomatic status, approximately 50% of individuals who test positive for SARS-CoV-2 seem to be in non-infectious phases of the disease, based on having low viral loads in a range from which live virus has rarely been isolated. We find that, at any given time, just 2% of individuals carry 90% of the virions circulating within communities, serving as viral "super-carriers" and possibly also super-spreaders.

Junko Kurita, Yoshiyuki Sugishita, Tamie Sugawara, Yasushi Ohkusa

Background: Countermeasures against COVID-19 outbreak such as lockdown and voluntary restrictions against going out adversely affect human stress and economic activity. Particularly, this stress might lead to suicide. Object: We examined excess mortality attributable to suicide caused by COVID-19. Method: We applied the NIID model to suicide deaths from October 2009 through November, 2020 for the whole of Japan for both genders. Effects of the great earthquake that struck in eastern Japan on March 11, 2011 were incorporated into the estimation model. Results: Significant excess mortality in suicide was found between July and November in 2020 for both genders. It was greater among females than among males. In total, 1599 excess cases of mortality were identified. Discussion and Conclusion: Excess mortality during the four months was more than two times greater than the number of COVID-19 deaths confirmed by PCR testing. Countermeasures against COVID-19 should be chosen carefully in light of suicide effects.

Margarita Pons-Salort, Jacob John, Oliver John Watson, Nicholas F Brazeau, Robert Verity, Gagandeep Kang, Nicholas C. Grassly

India reported over 10 million COVID-19 cases and 149,000 deaths in 2020. To estimate exposure and the potential for further spread, we used a SARS-CoV-2 transmission model fit to seroprevalence data from three serosurveys in Delhi and the time-series of reported deaths to reconstruct the epidemic. The cumulative proportion of the population estimated infected was 48.7% (95% CrI 22.1% - 76.8%) by end-September 2020. Using an age-adjusted overall infection fatality ratio (IFR) based on age-specific estimates from mostly high-income countries (HICs), we estimate that 15.0% (95% CrI 9.3% - 34.0%) of COVID-19 deaths were reported. This indicates either under-reporting of COVID-19 deaths and/or a lower age-specific IFR in India compared with HICs. Despite the high attack rate of SARS-CoV-2, a third wave occurred in late 2020, suggesting that herd immunity was not yet reached. Future dynamics will strongly depend on the duration of immunity and protection against new variants.

Marc SOURIS, Léon TSHILOLO, Daniel PARZY, Rachel KAMGAING, Destin MBONGI, Balthazar PHOBA, Marie-Anasthasie TSHILOLO, René MBUNGU, Pierre MORAND, Jean-Paul GONZALEZ

More than a year after the emergence of COVID-19, significant regional differences in terms of morbidity persist, showing lower incidence rates in sub-Saharan Africa, Southeast Asia, and Oceania. Like SARS-CoV-1 and MERS viruses, SARS-CoV-2 is monophyletically positioned with parental species of chiropteran coronavirus. Furthermore, we observe that the spatial distribution of several targeted bat species (i.e., Coronavirus species hosts) overlaps the distribution of countries with low COVID-19 incidence. The work presented here aims to test the presence of natural immunity among population with a low COVD-19 prevalence, potentially due to a previous exposure to coronavirus antigens of a virus close related to SARS-CoV-2. To identify such pre-existing immunity, an ELISA serological test was used to detect IgG antibodies targeting main SARS-CoV-2 proteins including: the N-protein, the Spike 1 (S1) protein, the receptor binding domain (RBD) of the S1 protein, the N-terminal domain (NTD) of the S1 protein, and the S2 protein. A total of 574 sera samples collected before 2019 in the population of the Democratic Republic of Congo (DRC) were tested). 189 control sera from blood donors in France were used as control samples. The results showed a statistically significant difference between the DRC samples and control samples for all antigens (N, S1, S2, NTD) except for RBD. The percentage of positive samples presenting reactive antibodies for S1 antigen was respectively of 19.2% for RDC versus 2.11% for the control, and of 9.3% versus 1.6% for the S2 antigen. In conclusion, our data showed that the study population has been potentially exposed to a SARS-CoV-2-like virus antigen before the pandemic in the Central African sub-region. Therefore, it is quite legitimate to think that this prior immunity may be protective and responsible for the observed low prevalence of COVID-19. Moreover, we can assume that this not yet identified SARS-CoV-2-like could be associated to a chiropteran species in close contact with the studied population. In order to confirm the presence of SARS-CoV-2-like virus antibodies and ultimately identify the neutralizing potential for the detected antibodies, our study is underway in other African and Asian countries, where the COVID-19 prevalence is limited.

Ruediger Gross, Michelle Zanoni, Alina Seidel, Carina Conzelmann, Andrea Gilg, Daniela Krnavek, Suemeyye Erdemci-evin, Benjamin Mayer, Markus Hoffmann, Stefan Poehlmann, Alexandra Beil, Joris Kroschel, Bernd Jahrsdoerfer, Hubert Schrezenmeier, Frank Kirchhoff, Jan Muench, Janis A Mueller

Background Heterologous prime-boost schedules with vector- and mRNA-based COVID-19 vaccines are already administered, but immunological responses and elicited protection have not been reported. Methods We here analyzed a cohort of 26 individuals aged 25-46 (median 30.5) years that received a ChAdOx1 nCoV-2019 prime followed by a BNT162b2 boost after an 8-week interval for reactogenicity, antibody responses and T cell reactivity. Results Self-reported solicited symptoms after ChAdOx1 nCoV-2019 prime were in line with previous reports and less severe after the BNT162b2 boost. Antibody titers increased significantly over time resulting in strong neutralization titers 2 weeks after the BNT162b2 boost. Neutralizing activity against the prevalent strain B.1.1.7 was 3.9-fold higher than in individuals receiving homologous BNT162b2 vaccination, only 2-fold reduced for variant of concern B.1.351, and similar for variant B.1.617. In addition, CD4+ and CD8+ T cells reacted to SARS-CoV-2 spike peptide stimulus 2 weeks after the full vaccination. Conclusions The heterologous ChAdOx1 nCoV-2019 / BNT162b2 prime-boost vaccination regimen is not associated with serious adverse events and results in a potent humoral immune response and elicits T cell reactivity. Variants of concern B.1.1.7, B.1.351 and B.1.617 are potently neutralized by sera of all participants. These results suggest that this heterologous vaccination regimen is at least as immunogenic and protective as homologous vaccinations.

David Hillus, Tatjana Schwarz, Pinkus Tober-Lau, Hana Hastor, Charlotte Thibeault, Stefanie Kasper, Elisa T. Helbig, Lena J. Lippert, Patricia Tscheak, Marie Luisa Schmidt, Johanna Riege, Andr Solarek, Christof von Kalle, Chantip Dang-Heine, Piotr Kopankiewicz, Norbert Suttorp, Christian Drosten, Harald Bias, Joachim Seybold, COVIM/EICOV Study Group, Florian Kurth, Victor M Corman, Leif Erik Sander

Objective: to assess reactogenicity and immunogenicity of heterologous prime-boost immunisations of ChAdOx1-nCoV19 (Vaxzevria, ChAdOx) followed by BNT162b2 (Comirnaty, BNT) compared to homologous BNT/BNT immunisation. Design: prospective, observational cohort study. Setting: unicenter study in a cohort of health care workers at a tertiary care center in Berlin, Germany. Participants: 340 health care workers immunised between 27 December 2020 and 21 May 2021 at Charite - Universitaetsmedizin Berlin, Germany Main outcome measures: the main outcomes were reactogenicity assessed on days one, three, five and seven post prime and boost vaccination, and immunogenicity measured by serum SARS-CoV-2 full spike-, spike S1-, and spike RBD-IgG, virus neutralisation capacity, anti-S1-IgG avidity, and T cell reactivity measured by Interferon gamma release assay at 3-4 weeks post prime and boost immunisation. Results: Heterologous ChAdOx/BNT booster vaccination was overall well-tolerated and reactogenicity was largely comparable to homologous BNT/BNT vaccination. Systemic reactions were most frequent after prime immunisation with ChAdOx (86%, 95CI: 79-91), and less frequent after homologous BNT/BNT (65%, 95CI: 56-72), or heterologous ChAdOx/BNT booster vaccination (48%, 95CI: 36-59). Serum antibody responses and T cell reactivity were strongly increased after both homologous and heterologous boost, and immunogenicity was overall robust, and comparable between both regimens in this cohort, with slightly increased S1-IgG avidity and T cell responses following heterologous booster immunisation. Conclusions: Evidence of rare thrombotic events associated with ChAdOx has led to recommendation of a heterologous booster with mRNA vaccines for certain age groups in several European countries, despite a lack of robust safety and immunogenicity data for this vaccine regimen. This interim analysis provides evidence that the currently recommended heterologous ChAdOx/BNT immunisation regimen with 10-12 week vaccine intervals is well tolerated and slightly more immunogenic compared to homologous BNT/BNT vaccination with three week vaccine intervals. Heterologous prime-boost immunisation for COVID-19 may be generally applicable to optimise logistics and improve immunogenicity and to mitigate potential intermittent supply shortages for individual vaccines.

Kristen W Cohen, Susanne L. Linderman, Zoe Moodie, Julie Czartoski, Lilin Lai, Grace Mantus, Carson Norwood, Lindsay E. Nyhoff, Venkata Viswanadh Edara, Katharine Floyd, Stephen C De Rosa, Hasan Ahmed, Rachael Whaley, Shivan N. Patel, Brittany Prigmore, Maria P Lemos, Carl W Davis, Sarah Furth, James O'Keefe, Mohini P. Gharpure, Sivaram Gunisetty, Kathy A. Stephens, Rustom Antia, Veronika I Zarnitsyna, David S Stephens, Srilatha Edupuganti, Nadine Rouphael, Evan J. Anderson, Aneesh K. Mehta, Jens Wrammert, Mehul S Suthar, Rafi Ahmed, M Juliana McElrath

Ending the COVID-19 pandemic will require long-lived immunity to SARS-CoV-2. We evaluated 254 COVID-19 patients longitudinally from early infection and for eight months thereafter and found a predominant broad-based immune memory response. SARS-CoV-2 spike binding and neutralizing antibodies exhibited a bi-phasic decay with an extended half-life of >200 days suggesting the generation of longer-lived plasma cells. In addition, there was a sustained IgG+ memory B cell response, which bodes well for a rapid antibody response upon virus re-exposure. Polyfunctional virus-specific CD4+ and CD8+ T cells were also generated and maintained with an estimated half-life of 200 days. Interestingly, the CD4+ T cell response equally targeted several SARS-CoV-2 proteins, whereas the CD8+ T cell response preferentially targeted the nucleoprotein, highlighting the importance of including the nucleoprotein as a potential vaccine antigen. Taken together, these results suggest that broad and effective immunity may persist long-term in recovered COVID-19 patients.

Ariel Karlinsky, Dmitry Kobak

Comparing the impact of the COVID-19 pandemic between countries or across time is difficult because the reported numbers of cases and deaths can be strongly affected by testing capacity and reporting policy. Excess mortality, defined as the increase in all-cause mortality relative to the recent average, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no central, frequently-updated repository of the all-cause mortality data across countries. To fill this gap, we have collected weekly, monthly, or quarterly all-cause mortality data from 77 countries, openly available as the regularly-updated World Mortality Dataset. We used this dataset to compute the excess mortality in each country during the COVID-19 pandemic. We found that in the worst-affected countries the annual mortality increased by over 50%, while in several other countries it decreased by over 5%, presumably due to lockdown measures decreasing the non-COVID mortality. Moreover, we found that while some countries have been reporting the COVID-19 deaths very accurately, many countries have been underreporting their COVID-19 deaths by an order of magnitude or more. Averaging across the entire dataset suggests that the world's COVID-19 death toll may be at least 1.6 times higher than the reported number of confirmed deaths.

Julie E. Horowitz, Jack A. Kosmicki, Amy Damask, Deepika Sharma, Genevieve H. L. Roberts, Anne A. E. Justice, Nilanjana Banerjee, Marie V. Coignet, Ashish Yadav, Joseph B Leader, Anthony Marcketta, Danny S. Park, Rouel Lanche, Evan Maxwell, Spencer C. Knight, Xiaodong Bai, Harenda Guturu, Dylan Sun, Asher Baltzell, Fabricio S. P. Kury, Joshua D Backman, Ahna R. Girshick, Colm O'Dushlaine, Shannon R. McCurdy, Raghavendran Partha, Adam J Mansfield, David A Turissini, Alexander H Li, Miao Zhang, Joelle Mbatchou, Kyoko Watanabe, Lauren Gurski, Shane E McCarthy, Hyun Min Kang, Lee Dobbyn, Eli Stahl, Anurag Verma, Giorgio Sirugo, Regeneron Genetics Center, Marylyn D. Ritchie, Marcus Jones, Suganthi Balasubramanian, Katherine Siminovitch, William J. Salerno, Alan R. Shuldiner, Daniel J. Rader, Tooraj Mirshahi, Adam E Locke, Jonathan Marchini, John D Overton, David J Carey, Lukas Habegger, Michael N Cantor, Kristin A. Rand, Eurie L. Hong, Jeffrey G. Reid, Catherine A Ball, Aris Baras, Goncalo R. Abecasis, Manuel A. Ferreira

SARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5x10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.

Matteo Sesia, Stephen Bates, Emmanuel Candès, Jonathan Marchini, Chiara Sabatti

We present a comprehensive statistical framework to analyze data from genome-wide association studies of polygenic traits, producing distinct and interpretable discoveries while controlling the false discovery rate. This approach leverages sophisticated multivariate models, correcting for linkage disequilibrium, and accounts for population structure and relatedness, adapting to the characteristics of the samples at hand. A key element is the recognition that the observed genotypes can be considered as a random sample from an appropriate model, encapsulating our knowledge of genetic inheritance and human populations. This allows us to generate imperfect copies (knockoffs) of these variables which serve as ideal negative controls; knockoffs are indistinguishable from the original genotypes in distribution, and independent from the phenotype. In sharp contrast with state-of-the-art methods, the validity of our inference in no way depends on assumptions about the unknown relation between genotypes and phenotype. We develop and leverage a model for the genotypes that accounts for arbitrary and unknown population structure, which may be due to diverse ancestries or familial relatedness. We build a pipeline that is robust to the most prominent possible confounders, facilitating the discovery of causal variants. Validity and effectiveness are demonstrated by extensive simulations with real data, as well as by the analysis of several phenotypes in the UK Biobank. Finally, fast software is made available for researchers to apply the proposed methodology to Biobank-scale data sets.

Marion Darnaud, Filipe De Vadder, Pascaline Bogeat, Lilia Boucinha, Anne-Laure Bulteau, Andrei Bunescu, Celine Couturier, Ana Delgado, Helene Dugua, Celine Elie, Alban Mathieu, Tereza Novotna, Djomangan Adama Ouattara, Severine Planel, Adrien Saliou, Dagmar Srutkova, Jennifer Yansouni, Barbel Stecher, Martin Schwarzer, Francois Leulier, Andrea Tamellini

Mus musculus is the classic mammalian model for biomedical research. Despite global efforts to standardize breeding and experimental procedures, the undefined composition and interindividual diversity of the microbiota of laboratory mice remains a limitation. In an attempt to standardize the gut microbiome in preclinical mouse studies, we developed a simplified mouse microbiota composed of 15 strains from 7 of the 20 most prevalent bacterial families representative of the fecal microbiota of C57BL/6J Specific (and Opportunistic) Pathogen-Free (SPF/SOPF) animals and derived a new standardized gnotobiotic mouse model called GM15. GM15 recapitulates extensively the functionalities found in the C57BL/6J SOPF microbiota metagenome, and GM15 animals are phenotypically similar to SOPF or SPF animals in two different facilities. They are also less sensitive to the deleterious effects of post-weaning malnutrition. The GM15 model provides increased reproducibility and robustness of preclinical studies by limiting the confounding effect of fluctuation in microbiota composition, and offers new opportunities for research focused on how the microbiota shapes host physiology in health and disease.

Yair Goldberg, Micha Mandel, Yonatan Woodbridge, Ronen Fluss, Ilya Novikov, Rami Yaari, Arnona Ziv, Laurence Freedman, Amit Huppert

Worldwide shortage of vaccination against SARS-CoV-2 infection while the pandemic is still uncontrolled leads many states to the dilemma whether or not to vaccinate previously infected persons. Understanding the level of protection of previous infection compared to that of vaccination is critical for policy making. We analyze an updated individual-level database of the entire population of Israel to assess the protection efficacy of both prior infection and vaccination in preventing subsequent SARS-CoV-2 infection, hospitalization with COVID-19, severe disease, and death due to COVID-19. Vaccination was highly effective with overall estimated efficacy for documented infection of 92.8% (CI: [92.6, 93.0]); hospitalization 94.2% (CI: [93.6, 94.7]); severe illness 94.4% (CI: [93.6, 95.0]); and death 93.7% (CI: [92.5, 94.7]). Similarly, the overall estimated level of protection from prior SARS-CoV-2 infection for documented infection is 94.8% (CI: [94.4, 95.1]); hospitalization 94.1% (CI: [91.9, 95.7]); and severe illness 96.4% (CI: [92.5, 98.3]). Our results question the need to vaccinate previously-infected individuals.

Diana Tavares-Ferreira, Stephanie Shiers, Pradipta Ray, Andi Wangzhou, Vivekanand Jeevakumar, Ishwarya Sankaranarayanan, Anna Cervantes, Jeffrey C. Reese, Alexander Chamessian, Bryan Copits, Patrick M. Dougherty, Robert Gereau, Michael D Burton, Gregory Dussor, Theodore J Price

Nociceptors are specialized sensory neurons that detect damaging or potentially damaging stimuli and are found in the dorsal root (DRG) and trigeminal ganglia. These neurons are critical for the generation of neuronal signals that ultimately create the perception of pain. These neurons are also primary targets for acute and chronic pain therapeutics. Single-cell transcriptomics on mouse nociceptors has transformed our understanding of pain mechanisms. We sought to generate equivalent information for human nociceptors with the goal of identifying transcriptomic signatures of nociceptors, identifying species differences and elucidating new drug targets. We used spatial transcriptomics to molecularly characterize transcriptomes of single dorsal root ganglion (DRG) neurons from 8 organ donors. We identified 12 clusters of human sensory neurons, 5 of which are C nociceptors; as well as 1 Abeta; nociceptor, 2 Adelta;, 2 Abeta; and 1 proprioceptor subtypes. By focusing on expression profiles for ion channels, G-protein coupled receptors (GPCRs) and other pharmacological targets, we provide a rich map of drug targets in the human DRG with direct comparison to mouse sensory neuron transcriptomes. We also compare human DRG neuronal subtypes to non-human primates showing conserved patterns of gene expression among many cell types, but divergence among specific nociceptor subsets. Finally, we identify sex differences in human DRG subpopulation transcriptomes, including a marked increase in CALCA expression in female pruritogen receptor enriched nociceptors. Our data open the door to development of drug discovery programs for new pain targets and unparalleled molecular characterization of clinical sensory disorders.

Leonardo Nicola Martin Iasi, Harald Ringbauer, Benjamin Marco Peter

Neandertal DNA makes up 2-3% of the genomes of all non-African individuals. The patterns of Neandertal ancestry in modern humans have been used to estimate that this is the result of gene flow that occurred during the expansion of modern humans into Eurasia, but the precise dates of this event remain largely unknown. Here, we introduce an extended admixture pulse model that allows joint estimation of the timing and duration of gene flow. This model leads to simple expressions for both the admixture segment distribution and the decay curve of ancestry linkage disequilibrium, and we show that these two statistics are closely related. In simulations, we find that estimates of the mean time of admixture are largely robust to details in gene flow models, but that the duration of the gene flow can only be recovered if gene flow is very recent and the exact recombination map is known. These results imply that gene flow from Neandertals into modern humans could have happened over hundreds of generations. Ancient genomes from the time around the admixture event are thus likely required to resolve the question when, where, and for how long humans and Neandertals interacted.

MICHAEL SKUHERSKY, Tailin Wu, Eviatar Yemini, Edward Boyden, Max Tegmark

Determining cell identity in volumetric images of tagged neuronal nuclei is an ongoing challenge in contemporary neuroscience. Frequently, cell identity is determined by aligning and matching tags to an "atlas" of labeled neuronal positions and other identifying characteristics. Previous analyses of such C. elegans datasets have been hampered by the limited accuracy of such atlases, especially for neurons present in the ventral nerve cord, and also by time-consuming manual elements of the alignment process. We present a novel automated alignment method for sparse and incomplete point clouds of the sort resulting from typical C. elegans fluorescence microscopy datasets. This method involves a tunable learning parameter and a kernel that enforces biologically realistic deformation. We also present a pipeline for creating alignment atlases from datasets of the recently developed NeuroPAL transgene. In combination, these advances allow us to label neurons in volumetric images with confidence much higher than previous methods. We release, to the best of our knowledge, the most complete C. elegans 3D positional neuron atlas, encapsulating positional variability derived from 7 animals, for the purposes of cell-type identity prediction for myriad applications (e.g., imaging neuronal activity, gene expression, and cell-fate).

Artem Kaznatcheev

Valiant (2009) proposed to treat Darwinian evolution as a special kind of computational learning from statistical queries. The statistical queries represent a genotype's fitness over a distribution of challenges. And this distribution of challenges along with the best response to them specify a given abiotic environment or static fitness landscape. Valiant's model distinguished families of environments that are "adaptable-to" from those that are not. But this model of evolution omits the vital ecological interactions between different evolving agents -- it neglects the rich biotic environment that is central to the struggle for existence. In this article, I extend algorithmic Darwinism to include the ecological dynamics of frequency-dependent selection as a population-dependent bias to the distribution of challenges that specify an environment. Thus, extended algorithmic Darwinism suggests extended statistical queries rather than just statistical queries as the appropriate model for eco-evo dynamics. This extended algorithmic Darwinism replaces simple invasion of wild-type by a mutant-type of higher scalar fitness with an evolutionary game between wild-type and mutant-type based on their frequency-dependent fitness function. To analyze this model, I develop a game landscape view of evolution, as a generalization of the classic fitness landscape approach. I show that this model of eco-evo dynamics on game landscapes can provide an exponential speed-up over the purely evolutionary dynamics of the strict algorithmic Darwinism. In particular, I prove that the Parity environment -- which is known to be not adaptable-to under strict algorithmic Darwinism -- is adaptable-to by eco-evo dynamics. Thus, the ecology of frequency-dependent selection does not just increase the tempo of evolution, but fundamentally transforms its mode. This happens even if frequency-dependence is restricted to short-time scales -- such short bursts of frequency-dependent selection can have a transformative effect on the ability of populations to adapt to their environments in the long-term. Unlike typical learning algorithms, the eco-evo dynamic for adapting to the Parity environment does not rely on Gaussian elimination. Instead, the dynamics proceed by simple isotropic mutations and selection in finite populations of just two types (the resident wild-type and invading mutant). The resultant process has two stages: (1) a quick stage of point-mutations that moves the population to one of exponentially many local fitness peaks; followed by (2) a slower stage where each 'step' follows a double-mutation by a point-mutation. This second stage allows the population to hop between local fitness peaks to reach the unique global fitness peak in polynomial time. The evolutionary game dynamics of finite populations are essential for finding a short adaptive path to the global fitness peak during the second stage of the adaptation process. This highlights the rich interface between computational learning theory, analysis of algorithms, evolutionary games, and long-term evolution.

Jakub M Bartoszewicz, Ulrich Genske, Bernhard Y Renard

Novel pathogens evolve quickly and may emerge rapidly, causing dangerous outbreaks or even global pandemics. Next-generation sequencing is the state-of-the-art in open-view pathogen detection, and one of the few methods available at the earliest stages of an epidemic, even when the biological threat is unknown. Analyzing the samples as the sequencer is running can greatly reduce the turnaround time, but existing tools rely on close matches to lists of known pathogens and perform poorly on novel species. Machine learning approaches can predict if single reads originate from more distant, unknown pathogens, but require relatively long input sequences and processed data from a finished sequencing run. Incomplete sequences contain less information, leading to a trade-off between sequencing time and detection accuracy. Using a workflow for real-time pathogenic potential prediction, we investigate which subsequences already allow accurate inference. We train deep neural networks to classify Illumina and Nanopore reads and integrate the models with HiLive2, a real-time Illumina mapper. This approach outperforms alternatives based on machine learning and sequence alignment on simulated and real data, including SARS-CoV-2 sequencing runs. After just 50 Illumina cycles, we observe an 80-fold sensitivity increase compared to real-time mapping. The first 250bp of Nanopore reads, corresponding to 0.5s of sequencing time, are enough to yield predictions more accurate than mapping the finished long reads. The approach could also be used for screening synthetic sequences against biosecurity threats.

Dami A Collier, Anna De Marco, Isabella A.T.M. Ferreira, Bo Meng, Rawlings Datir, Alexandra C. Walls, Steven A. Kemp S, Jessica Bassi, Dora Pinto, Chiara Silacci Fregni, Siro Bianchi, M. Alejandra Tortorici, John Bowen, Katja Culap, Stefano Jaconi, Elisabetta Cameroni, Gyorgy Snell, Matteo S. Pizzuto, Alessandra Franzetti Pellanda, Christian Garzoni, Agostino Riva, The CITIID-NIHR BioResource COVID-19 Collaboration, Anne Elmer, Nathalie Kingston, Barbara Graves, Laura McCoy, Kenneth G.C. Smith, John R Bradley, Nigel James Temperton, Lourdes Ceron-Gutierrez L, Gabriela Barcenas-Morales, The COVID-19 Genomics UK (COG-UK) consortium, William Harvey, Herbert W Virgin, Antonio Lanzavecchia, Luca Piccoli, Rainer Doffinger, Mark Wills, David Veesler, Davide Corti, Ravindra K Gupta

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) transmission is uncontrolled in many parts of the world, compounded in some areas by higher transmission potential of the B1.1.7 variant now seen in 50 countries. It is unclear whether responses to SARS-CoV-2 vaccines based on the prototypic strain will be impacted by mutations found in B.1.1.7. Here we assessed immune responses following vaccination with mRNA-based vaccine BNT162b2. We measured neutralising antibody responses following a single immunization using pseudoviruses expressing the wild-type Spike protein or the 8 amino acid mutations found in the B.1.1.7 spike protein. The vaccine sera exhibited a broad range of neutralising titres against the wild-type pseudoviruses that were modestly reduced against B.1.1.7 variant. This reduction was also evident in sera from some convalescent patients. Decreased B.1.1.7 neutralisation was also observed with monoclonal antibodies targeting the N-terminal domain (9 out of 10), the Receptor Binding Motif (RBM) (5 out of 31), but not in neutralising mAbs binding outside the RBM. Introduction of the E484K mutation in a B.1.1.7 background to reflect newly emerging viruses in the UK led to a more substantial loss of neutralising activity by vaccine-elicited antibodies and mAbs (19 out of 31) over that conferred by the B.1.1.7 mutations alone. E484K emergence on a B.1.1.7 background represents a threat to the vaccine BNT162b.