Delineating the functional activity of antibodies with cross-reactivity to SARS-CoV-2, SARS-CoV-1 and related sarbecoviruses.

The recurring spillover of pathogenic coronaviruses and demonstrated capacity of sarbecoviruses, such SARS-CoV-2, to rapidly evolve in humans underscores the need to better understand immune responses to this virus family. For this purpose, we characterized the functional breadth and potency of antibodies targeting the receptor binding domain (RBD) of the spike glycoprotein that exhibited cross-reactivity against SARS-CoV-2 variants, SARS-CoV-1 and sarbecoviruses from diverse clades and animal origins with spillover potential. One neutralizing antibody, C68.61, showed remarkable neutralization breadth against both SARS-CoV-2 variants and viruses from different sarbecovirus clades. C68.61, which targets a conserved RBD class 5 epitope, did not select for escape variants of SARS-CoV-2 or SARS-CoV-1 in culture nor have predicted escape variants among circulating SARS-CoV-2 strains, suggesting this epitope is functionally constrained. We identified 11 additional SARS-CoV-2/SARS-CoV-1 cross-reactive antibodies that target the more sequence conserved class 4 and class 5 epitopes within RBD that show activity against a subset of diverse sarbecoviruses with one antibody binding every single sarbecovirus RBD tested. A subset of these antibodies exhibited Fc-mediated effector functions as potent as antibodies that impact infection outcome in animal models. Thus, our study identified antibodies targeting conserved regions across SARS-CoV-2 variants and sarbecoviruses that may serve as therapeutics for pandemic preparedness as well as blueprints for the design of immunogens capable of eliciting cross-neutralizing responses.

Single B cell transcriptomics identifies multiple isotypes of broadly neutralizing antibodies against flaviviruses.

Sequential dengue virus (DENV) infections often generate neutralizing antibodies against all four DENV serotypes and sometimes, Zika virus. Characterizing cross-flavivirus broadly neutralizing antibody (bnAb) responses can inform countermeasures that avoid enhancement of infection associated with non-neutralizing antibodies. Here, we used single cell transcriptomics to mine the bnAb repertoire following repeated DENV infections. We identified several new bnAbs with comparable or superior breadth and potency to known bnAbs, and with distinct recognition determinants. Unlike all known flavivirus bnAbs, which are IgG1, one newly identified cross-flavivirus bnAb (F25.S02) was derived from IgA1. Both IgG1 and IgA1 versions of F25.S02 and known bnAbs displayed neutralizing activity, but only IgG1 enhanced infection in monocytes expressing IgG and IgA Fc receptors. Moreover, IgG-mediated enhancement of infection was inhibited by IgA1 versions of bnAbs. We demonstrate a role for IgA in flavivirus infection and immunity with implications for vaccine and therapeutic strategies.

AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets.

Analysis of an individual's immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes. We describe interoperability standards for germline sets, and an approach to transparency based on principles of findability, accessibility, interoperability, and reusability.

Reconstruction of a polyclonal ADCC antibody repertoire from an HIV-1 non-transmitting mother.

Human natural history and vaccine studies support a protective role of antibody dependent cellular cytotoxicity (ADCC) activity against many infectious diseases. One setting where this has consistently been observed is in HIV-1 vertical transmission, where passively acquired ADCC activity in HIV-exposed infants has correlated with reduced acquisition risk and reduced pathogenesis in HIV+ infants. However, the characteristics of HIV-specific antibodies comprising a maternal plasma ADCC response are not well understood. Here, we reconstructed monoclonal antibodies (mAbs) from memory B cells from late pregnancy in mother MG540, who did not transmit HIV to her infant despite several high-risk factors. Twenty mAbs representing 14 clonal families were reconstructed, which mediated ADCC and recognized multiple HIV Envelope epitopes. In experiments using Fc-defective variants, only combinations of several mAbs accounted for the majority of plasma ADCC of MG540 and her infant. We present these mAbs as evidence of a polyclonal repertoire with potent HIV-directed ADCC activity.

Single B cell transcriptomics identifies multiple isotypes of broadly neutralizing antibodies against flaviviruses.

Sequential dengue virus (DENV) infections often generate neutralizing antibodies against all four DENV serotypes and sometimes, Zika virus. Characterizing cross-flavivirus broadly neutralizing antibody (bnAb) responses can inform countermeasure strategies that avoid infection enhancement associated with non-neutralizing antibodies. Here, we used single cell transcriptomics to mine the bnAb repertoire following secondary DENV infection. We identified several new bnAbs with comparable or superior breadth and potency to known bnAbs, and with distinct recognition determinants. Unlike all known flavivirus bnAbs, which are IgG1, one newly identified cross-flavivirus bnAb (F25.S02) was derived from IgA1. Both IgG1 and IgA1 versions of F25.S02 and known bnAbs displayed neutralizing activity, but only IgG1 enhanced infection in monocytes expressing IgG and IgA Fc receptors. Moreover, IgG-mediated enhancement of infection was inhibited by IgA1 versions of bnAbs. We demonstrate a role for IgA in flavivirus infection and immunity with implications for vaccine and therapeutic strategies.

AIRR-C IG Reference Sets: curated sets of immunoglobulin heavy and light chain germline genes.

Introduction: Analysis of an individual's immunoglobulin (IG) gene repertoire requires the use of high-quality germline gene reference sets. When sets only contain alleles supported by strong evidence, AIRR sequencing (AIRR-seq) data analysis is more accurate and studies of the evolution of IG genes, their allelic variants and the expressed immune repertoire is therefore facilitated. Methods: The Adaptive Immune Receptor Repertoire Community (AIRR-C) IG Reference Sets have been developed by including only human IG heavy and light chain alleles that have been confirmed by evidence from multiple high-quality sources. To further improve AIRR-seq analysis, some alleles have been extended to deal with short 3' or 5' truncations that can lead them to be overlooked by alignment utilities. To avoid other challenges for analysis programs, exact paralogs (e.g. IGHV1-69*01 and IGHV1-69D*01) are only represented once in each set, though alternative sequence names are noted in accompanying metadata. Results and discussion: The Reference Sets include less than half the previously recognised IG alleles (e.g. just 198 IGHV sequences), and also include a number of novel alleles: 8 IGHV alleles, 2 IGKV alleles and 5 IGLV alleles. Despite their smaller sizes, erroneous calls were eliminated, and excellent coverage was achieved when a set of repertoires comprising over 4 million V(D)J rearrangements from 99 individuals were analyzed using the Sets. The version-tracked AIRR-C IG Reference Sets are freely available at the OGRDB website (https://ogrdb.airr-community.org/germline_sets/Human) and will be regularly updated to include newly observed and previously reported sequences that can be confirmed by new high-quality data.

Inference of B cell clonal families using heavy/light chain pairing information.

Next generation sequencing of B cell receptor (BCR) repertoires has become a ubiquitous tool for understanding the antibody-mediated immune response: it is now common to have large volumes of sequence data coding for both the heavy and light chain subunits of the BCR. However, until the recent development of high throughput methods of preserving heavy/light chain pairing information, these samples contained no explicit information on which heavy chain sequence pairs with which light chain sequence. One of the first steps in analyzing such BCR repertoire samples is grouping sequences into clonally related families, where each stems from a single rearrangement event. Many methods of accomplishing this have been developed, however, none so far has taken full advantage of the newly-available pairing information. This information can dramatically improve clustering performance, especially for the light chain. The light chain has traditionally been challenging for clonal family inference because of its low diversity and consequent abundance of non-clonal families with indistinguishable naive rearrangements. Here we present a method of incorporating this pairing information into the clustering process in order to arrive at a more accurate partition of the data into clonally related families. We also demonstrate two methods of fixing imperfect pairing information, which may allow for simplified sample preparation and increased sequencing depth. Finally, we describe several other improvements to the partis software package.

Functional development of a V3/glycan-specific broadly neutralizing antibody isolated from a case of HIV superinfection.

Stimulating broadly neutralizing antibodies (bnAbs) directly from germline remains a barrier for HIV vaccines. HIV superinfection elicits bnAbs more frequently than single infection, providing clues of how to elicit such responses. We used longitudinal antibody sequencing and structural studies to characterize bnAb development from a superinfection case. BnAb QA013.2 bound initial and superinfecting viral Env, despite its probable naive progenitor only recognizing the superinfecting strain, suggesting both viruses influenced this lineage. A 4.15 Å cryo-EM structure of QA013.2 bound to native-like trimer showed recognition of V3 signatures (N301/N332 and GDIR). QA013.2 relies less on CDRH3 and more on framework and CDRH1 for affinity and breadth compared to other V3/glycan-specific bnAbs. Antigenic profiling revealed that viral escape was achieved by changes in the structurally-defined epitope and by mutations in V1. These results highlight shared and novel properties of QA013.2 relative to other V3/glycan-specific bnAbs in the setting of sequential, diverse antigens.

Development of antibody-dependent cell cytotoxicity function in HIV-1 antibodies.

A prerequisite for the design of an HIV vaccine that elicits protective antibodies is understanding the developmental pathways that result in desirable antibody features. The development of antibodies that mediate antibody-dependent cellular cytotoxicity (ADCC) is particularly relevant because such antibodies have been associated with HIV protection in humans. We reconstructed the developmental pathways of six human HIV-specific ADCC antibodies using longitudinal antibody sequencing data. Most of the inferred naive antibodies did not mediate detectable ADCC. Gain of antigen binding and ADCC function typically required mutations in complementarity determining regions of one or both chains. Enhancement of ADCC potency often required additional mutations in framework regions. Antigen binding affinity and ADCC activity were correlated, but affinity alone was not sufficient to predict ADCC potency. Thus, elicitation of broadly active ADCC antibodies may require mutations that enable high-affinity antigen recognition along with mutations that optimize factors contributing to functional ADCC activity.

Nearly four decades after the human immunodeficiency virus (HIV for short) was first identified, the search for a vaccine still continues. An effective immunisation would require elements that coax the human immune system into making HIV-specific antibodies ­ the proteins that can recognise, bind to and deactivate the virus. Crucially, antibodies can also help white blood cells to target and destroy cells infected with HIV. This 'antibody-dependent cellular cytotoxicity' could be a key element of a successful vaccine, yet it has received less attention than the ability for antibodies to directly neutralize the virus. In particular, it is still unclear how antibodies develop the ability to flag HIV-infected cells for killing. Indeed, over the course of an HIV infection, an immune cell goes through genetic changes that tweak the 3D structure of the antibodies it manufactures. This process can improve the antibodies' ability to fight off the virus, but it was still unclear how it would shape antibody-dependent cellular cytotoxicity. To investigate this question, Doepker et al. retraced how the genes coding for six antibody families changed over time in an HIV-carrying individual. This revealed that antibodies could not initially trigger antibody-dependent cellular cytotoxicity. The property emerged and improved thanks to two types of alterations in the genetic sequences. One set of changes increased how tightly the antibodies could bind to the virus, targeting sections of the antibodies that can often vary. The second set likely altered the 3D structure in others ways, potentially affecting how antibodies bind the virus or how they interact with components of the immune system that help to kill HIV-infected cells. These alterations took place in segments of the antibodies that undergo less change over time. Ultimately, the findings by Doepker et al. suggest that an efficient HIV vaccine may rely on helping antibodies to evolve so they can bind more tightly to the virus and trigger cellular cytotoxicity more strongly.

Using B cell receptor lineage structures to predict affinity.

We are frequently faced with a large collection of antibodies, and want to select those with highest affinity for their cognate antigen. When developing a first-line therapeutic for a novel pathogen, for instance, we might look for such antibodies in patients that have recovered. There exist effective experimental methods of accomplishing this, such as cell sorting and baiting; however they are time consuming and expensive. Next generation sequencing of B cell receptor (BCR) repertoires offers an additional source of sequences that could be tapped if we had a reliable method of selecting those coding for the best antibodies. In this paper we introduce a method that uses evolutionary information from the family of related sequences that share a naive ancestor to predict the affinity of each resulting antibody for its antigen. When combined with information on the identity of the antigen, this method should provide a source of effective new antibodies. We also introduce a method for a related task: given an antibody of interest and its inferred ancestral lineage, which branches in the tree are likely to harbor key affinity-increasing mutations? We evaluate the performance of these methods on a wide variety of simulated samples, as well as two real data samples. These methods are implemented as part of continuing development of the partis BCR inference package, available at https://github.com/psathyrella/partis. Comments Please post comments or questions on this paper as new issues at https://git.io/Jvxkn.

A Bayesian phylogenetic hidden Markov model for B cell receptor sequence analysis.

The human body generates a diverse set of high affinity antibodies, the soluble form of B cell receptors (BCRs), that bind to and neutralize invading pathogens. The natural development of BCRs must be understood in order to design vaccines for highly mutable pathogens such as influenza and HIV. BCR diversity is induced by naturally occurring combinatorial "V(D)J" rearrangement, mutation, and selection processes. Most current methods for BCR sequence analysis focus on separately modeling the above processes. Statistical phylogenetic methods are often used to model the mutational dynamics of BCR sequence data, but these techniques do not consider all the complexities associated with B cell diversification such as the V(D)J rearrangement process. In particular, standard phylogenetic approaches assume the DNA bases of the progenitor (or "naive") sequence arise independently and according to the same distribution, ignoring the complexities of V(D)J rearrangement. In this paper, we introduce a novel approach to Bayesian phylogenetic inference for BCR sequences that is based on a phylogenetic hidden Markov model (phylo-HMM). This technique not only integrates a naive rearrangement model with a phylogenetic model for BCR sequence evolution but also naturally accounts for uncertainty in all unobserved variables, including the phylogenetic tree, via posterior distribution sampling.

Diversity and Function of Maternal HIV-1-Specific Antibodies at the Time of Vertical Transmission.

Infants of HIV-positive mothers can acquire HIV infection by various routes, but even in the absence of antiviral treatment, the majority of these infants do not become infected. There is evidence that maternal antibodies provide some protection from infection, but gestational maternal antibodies have not yet been characterized in detail. One of the most studied vertically infected infants is BG505, as the virus from this infant yielded an Envelope protein that was successfully developed as a stable trimer. Here, we isolated and characterized 39 HIV-specific neutralizing monoclonal antibodies (nAbs) from MG505, the mother of BG505, at a time point just prior to vertical transmission. These nAbs belonged to 21 clonal families and employed a variety of VH genes. Many were specific for the HIV-1 Env V3 loop, and this V3 specificity correlated with measurable antibody-dependent cellular cytotoxicity (ADCC) activity. The isolated nAbs did not recapitulate the full breadth of heterologous or autologous virus neutralization by contemporaneous plasma. Notably, we found that the V3-targeting nAb families neutralized one particular maternal Env variant, even though all tested variants had low V3 sequence diversity and were measurably bound by these nAbs. None of the nAbs neutralized BG505 transmitted virus. Furthermore, the MG505 nAb families were found at relatively low frequencies within the maternal B cell repertoire; all were less than 0.25% of total IgG sequences. Our findings illustrate an example of the diversity of HIV-1 nAbs within one mother, cumulatively resulting in a collection of antibody specificities that can contribute to the transmission bottleneck.IMPORTANCE Mother-to-child-transmission of HIV-1 offers a unique setting in which maternal antibodies both within the mother and passively transferred to the infant are present at the time of viral exposure. Untreated HIV-exposed human infants are infected at a rate of 30 to 40%, meaning that some infants do not get infected despite continued exposure to virus. Since the potential of HIV-specific immune responses to provide protection against HIV is a central goal of HIV vaccine design, understanding the nature of maternal antibodies may provide insights into immune mechanisms of protection. In this study, we isolated and characterized HIV-specific antibodies from the mother of an infant whose transmitted virus has been well studied.

sumrep: A Summary Statistic Framework for Immune Receptor Repertoire Comparison and Model Validation.

The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.

Per-sample immunoglobulin germline inference from B cell receptor deep sequencing data.

The collection of immunoglobulin genes in an individual's germline, which gives rise to B cell receptors via recombination, is known to vary significantly across individuals. In humans, for example, each individual has only a fraction of the several hundred known V alleles. Furthermore, the currently-accepted set of known V alleles is both incomplete (particularly for non-European samples), and contains a significant number of spurious alleles. The resulting uncertainty as to which immunoglobulin alleles are present in any given sample results in inaccurate B cell receptor sequence annotations, and in particular inaccurate inferred naive ancestors. In this paper we first show that the currently widespread practice of aligning each sequence to its closest match in the full set of IMGT alleles results in a very large number of spurious alleles that are not in the sample's true set of germline V alleles. We then describe a new method for inferring each individual's germline gene set from deep sequencing data, and show that it improves upon existing methods by making a detailed comparison on a variety of simulated and real data samples. This new method has been integrated into the partis annotation and clonal family inference package, available at https://github.com/psathyrella/partis, and is run by default without affecting overall run time.

Kappa chain maturation helps drive rapid development of an infant HIV-1 broadly neutralizing antibody lineage.

HIV-infected infants develop broadly neutralizing plasma responses with more rapid kinetics than adults, suggesting the ontogeny of infant responses could better inform a path to achievable vaccine targets. Here we reconstruct the developmental lineage of BF520.1, an infant-derived HIV-specific broadly neutralizing antibody (bnAb), using computational methods developed specifically for this purpose. We find that the BF520.1 inferred naive precursor binds HIV Env. We also show that heterologous cross-clade neutralizing activity evolved in the infant within six months of infection and that, ultimately, only 2% SHM is needed to achieve the full breadth of the mature antibody. Mutagenesis and structural analyses reveal that, for this infant bnAb, substitutions in the kappa chain were critical for activity, particularly in CDRL1. Overall, the developmental pathway of this infant antibody includes features distinct from adult antibodies, including several that may be amenable to better vaccine responses.

Inferred Allelic Variants of Immunoglobulin Receptor Genes: A System for Their Evaluation, Documentation, and Naming.

Immunoglobulins or antibodies are the main effector molecules of the B-cell lineage and are encoded by hundreds of variable (V), diversity (D), and joining (J) germline genes, which recombine to generate enormous IG diversity. Recently, high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) of recombined V-(D)-J genes has offered unprecedented insights into the dynamics of IG repertoires in health and disease. Faithful biological interpretation of AIRR-seq studies depends upon the annotation of raw AIRR-seq data, using reference germline gene databases to identify the germline genes within each rearrangement. Existing reference databases are incomplete, as shown by recent AIRR-seq studies that have inferred the existence of many previously unreported polymorphisms. Completing the documentation of genetic variation in germline gene databases is therefore of crucial importance. Lymphocyte receptor genes and alleles are currently assigned by the Immunoglobulins, T cell Receptors and Major Histocompatibility Nomenclature Subcommittee of the International Union of Immunological Societies (IUIS) and managed in IMGT®, the international ImMunoGeneTics information system® (IMGT). In 2017, the IMGT Group reached agreement with a group of AIRR-seq researchers on the principles of a streamlined process for identifying and naming inferred allelic sequences, for their incorporation into IMGT®. These researchers represented the AIRR Community, a network of over 300 researchers whose objective is to promote all aspects of immunoglobulin and T-cell receptor repertoire studies, including the standardization of experimental and computational aspects of AIRR-seq data generation and analysis. The Inferred Allele Review Committee (IARC) was established by the AIRR Community to devise policies, criteria, and procedures to perform this function. Formalized evaluations of novel inferred sequences have now begun and submissions are invited via a new dedicated portal (https://ogrdb.airr-community.org). Here, we summarize recommendations developed by the IARC-focusing, to begin with, on human IGHV genes-with the goal of facilitating the acceptance of inferred allelic variants of germline IGHV genes. We believe that this initiative will improve the quality of AIRR-seq studies by facilitating the description of human IG germline gene variation, and that in time, it will expand to the documentation of TR and IG genes in many vertebrate species.

AIRR Community Standardized Representations for Annotated Immune Repertoires.

Increased interest in the immune system's involvement in pathophysiological phenomena coupled with decreased DNA sequencing costs have led to an explosion of antibody and T cell receptor sequencing data collectively termed "adaptive immune receptor repertoire sequencing" (AIRR-seq or Rep-Seq). The AIRR Community has been actively working to standardize protocols, metadata, formats, APIs, and other guidelines to promote open and reproducible studies of the immune repertoire. In this paper, we describe the work of the AIRR Community's Data Representation Working Group to develop standardized data representations for storing and sharing annotated antibody and T cell receptor data. Our file format emphasizes ease-of-use, accessibility, scalability to large data sets, and a commitment to open and transparent science. It is composed of a tab-delimited format with a specific schema. Several popular repertoire analysis tools and data repositories already utilize this AIRR-seq data format. We hope that others will follow suit in the interest of promoting interoperable standards.

Likelihood-Based Inference of B Cell Clonal Families.

The human immune system depends on a highly diverse collection of antibody-making B cells. B cell receptor sequence diversity is generated by a random recombination process called "rearrangement" forming progenitor B cells, then a Darwinian process of lineage diversification and selection called "affinity maturation." The resulting receptors can be sequenced in high throughput for research and diagnostics. Such a collection of sequences contains a mixture of various lineages, each of which may be quite numerous, or may consist of only a single member. As a step to understanding the process and result of this diversification, one may wish to reconstruct lineage membership, i.e. to cluster sampled sequences according to which came from the same rearrangement events. We call this clustering problem "clonal family inference." In this paper we describe and validate a likelihood-based framework for clonal family inference based on a multi-hidden Markov Model (multi-HMM) framework for B cell receptor sequences. We describe an agglomerative algorithm to find a maximum likelihood clustering, two approximate algorithms with various trade-offs of speed versus accuracy, and a third, fast algorithm for finding specific lineages. We show that under simulation these algorithms greatly improve upon existing clonal family inference methods, and that they also give significantly different clusters than previous methods when applied to two real data sets.

Consistency of VDJ Rearrangement and Substitution Parameters Enables Accurate B Cell Receptor Sequence Annotation.

VDJ rearrangement and somatic hypermutation work together to produce antibody-coding B cell receptor (BCR) sequences for a remarkable diversity of antigens. It is now possible to sequence these BCRs in high throughput; analysis of these sequences is bringing new insight into how antibodies develop, in particular for broadly-neutralizing antibodies against HIV and influenza. A fundamental step in such sequence analysis is to annotate each base as coming from a specific one of the V, D, or J genes, or from an N-addition (a.k.a. non-templated insertion). Previous work has used simple parametric distributions to model transitions from state to state in a hidden Markov model (HMM) of VDJ recombination, and assumed that mutations occur via the same process across sites. However, codon frame and other effects have been observed to violate these parametric assumptions for such coding sequences, suggesting that a non-parametric approach to modeling the recombination process could be useful. In our paper, we find that indeed large modern data sets suggest a model using parameter-rich per-allele categorical distributions for HMM transition probabilities and per-allele-per-position mutation probabilities, and that using such a model for inference leads to significantly improved results. We present an accurate and efficient BCR sequence annotation software package using a novel HMM "factorization" strategy. This package, called partis (https://github.com/psathyrella/partis/), is built on a new general-purpose HMM compiler that can perform efficient inference given a simple text description of an HMM.

Exact identity for nonlinear wave propagation.

An exact identity for nonlinear sound wave propagation in one-dimensional media is shown to apply under a wide variety of conditions. The evidence suggests that this is true whenever there is a single input and output channel on each side of the medium, which can generally be achieved using monochromatic filters. It is shown mathematically that the identity cannot be derived from this condition and the known symmetries of the system. The question of what hidden symmetries in the system lead to the identity, and whether it applies even more generally to light waves, remains unresolved.