Biology subjects

Schmidt, F.

Publications and source records attributed to Schmidt, F..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Single-cell transcriptomics-guided development of flow cytometric tests predicting chronic myeloid leukemia blast crisis transformation at chronic phase diagnosis

Clinical risk scores in chronic myeloid leukemia (CML) are inadequate for identifying chronic phase (CP) patients at high-risk of blast crisis (BC) progression. The lack of accurate predictive tests hamper timely interventions, including stem cell transplants, that are more effective in early disease. By interrogating a single cell atlas of primary imatinib resistance for a BC-like gene expression signature, we identify aberrant CD42A+ megakaryocytic and CD10+CD19+ lymphoid progenitor expansion, as well as STAT1- and IFN{gamma}-related inflammatory programs, as consistent features in the bone marrow and peripheral blood of CP patients at high-risk of BC transformation. We develop multi-color flow cytometry-based tests (MFC) to detect these features in CP patients at the time of diagnosis. Validating our MFC panels on a combined Australia-Singapore cohort comprising 28 CP patients, including 14 who underwent transformation, we demonstrate their ability to detect 100% of CP patients who transform with no false positives. Our findings highlight small populations of inflamed hematopoietic stem and progenitor cells, present at CP diagnosis, as powerful harbingers of future BC transformation. The ability of MFC panels to detect these cells at diagnosis support their inclusion as accurate risk-assessment tools to improve management of high-risk patients.

cancer biology↗

bioRxiv2024

Macrophages expressing chimeric cytokine receptors have an inflammatory phenotype and anti-tumoral activity upon IL-10 or TGFβ stimulation

BackgroundTriple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer that lacks hormone receptors and HER2 amplification, making it unresponsive to standard hormone or HER2-targeted therapies. Although immune checkpoint inhibitors (ICIs) have shown promise in tumors with high lymphocyte infiltration, their efficacy remains limited in tumors with minimal lymphocyte infiltration. To overcome this challenge, we developed a novel approach to reprogram tumor-associated macrophages (TAMs) from an immunosuppressive to an inflammatory phenotype within the tumor microenvironment (TME), aiming to enhance therapeutic outcomes in TNBC. MethodsWe designed a chimeric cytokine receptor (ChCR) that triggers STAT1 signaling upon stimulation with IL-10 or TGF{beta}, cytokines prevalent in the TME that typically drive immunosuppression. Human primary macrophages were transduced with a lentiviral vector expressing the ChCR. Changes in their phenotype, secretome, and transcriptome were analyzed following stimulation. The anti-tumoral activity of these reprogrammed macrophages was assessed using co-culture assays with 3D TNBC spheroids. ResultsChCR-expressing macrophages showed robust STAT1 activation in response to IL-10 or TGF{beta} stimulation, resulting in an inflammatory phenotype similar to IFN{gamma} activation, as confirmed by phenotypic markers, and transcriptomic profiling. These ChCR-stimulated macrophages demonstrated significant anti-tumoral effects in 3D TNBC spheroids. Moreover, ChCR stimulation led to the upregulation of CXCL9 and CXCL10, chemokines essential for lymphocyte recruitment, and genes associated with good response to ICIs. ConclusionWe successfully engineered ChCRs that reprogram TAMs within an IL-10- and TGF{beta}-rich environment, inducing an inflammatory phenotype and anti-tumoral activity. The expression of CXCL9 and CXCL10 further supports lymphocyte recruitment, potentially facilitating greater lymphocyte infiltration and disrupting the immunosuppressive TME. This approach offers a promising strategy to improve immunotherapy outcomes in TNBC patients, particularly those with low immune cell infiltration, thereby addressing a critical unmet clinical need. What is already known on this topic Low T cell infiltration in triple negative breast cancer is associated with bad prognosis and non-responsiveness to immune checkpoint inhibitor in combination with chemotherapy. The presence of macrophages with an inflammatory phenotype is associated with T cell infiltration and better prognosis. The tumor microenvironment (TME), however, is rich in immunosuppressive cytokines like IL-10 and TGF{beta}, rendering macrophages immunosuppressive. Thus, reprogramming macrophages in the TME could benefit patients with low T cell infiltration. What this study adds We have designed a chimeric cytokine receptors (ChCR) that bind IL-10 or TGF{beta} and induces an IFN{gamma}-like inflammatory signaling and thus utilizes the local presence of immunosuppressive cytokines to reprogram macrophages. ChCR expressing macrophages show an inflammatory phenotype in the presence of immunosuppressive cytokines IL-10 or TGF{beta} and have an anti-tumoral activity in vitro. How this study might affect research, practice or policy - Our study is a starting point to explore ChCR-expressing macrophages as an adoptive cell therapy. Such therapy has the potential to attract T cells into the tumor and thereby boost the adaptive anti-tumoral immune response and response to immune checkpoint inhibitors. Moreover, our data suggest that such genetically-engineered macrophages have direct anti-tumoral activity.

immunology↗

bioRxiv2024

Eye Movements in Silent Visual Speech track Unheard Acoustic Signals and Relate to Hearing Experience

Behavioral and neuroscientific studies have shown that watching a speakers lip movements aids speech comprehension. Intriguingly, even when videos of speakers are presented silently, various cortical regions track auditory features, such as the envelope. Recently, we demonstrated that eye movements track low-level acoustic information when attentively listening to speech. In this study we investigated whether ocular speech tracking occurs during visual speech and how it influences cortical silent speech tracking. Furthermore, we compared the data of hearing individuals with congenitally deaf individuals, and those with acquired deafness or hearing loss (DHH; Deaf or hard of hearing) to assess how auditory deprivation (early vs. late onset) affects neural and ocular speech tracking during silent lip-reading. Using magnetoencephalography (MEG), we examined ocular and neural speech tracking of 75 participants observing silent videos of a speaker played forward and backward. Our main finding is a clear ocular unheard speech tracking effect with a dominance <1 Hz, which was not present for the lip movements. Similarly, we observed a <=1.3 Hz effect of neural unheard speech tracking in temporal regions for hearing participants. Importantly, neural tracking was not directly linked to ocular tracking in this study. Strikingly, across different listening groups, deaf participants with auditory listening experience showed higher ocular speech tracking than hearing participants, while no ocular speech tracking effect was revealed for congenitally deaf participants in a very small sample. This study extends our previous work by demonstrating the involvement of eye movements in speech processing, even in the absence of acoustic input.

neuroscience↗

bioRxiv2024

Accurate, fast and memory efficient quantification of immune cell phenotypes in cytometry using machine learning

To achieve accurate and reproducible cytometry data analysis, we benchmarked 19 machine learning algorithms for supervised and unsupervised cell classification. The underlying data encompassed 138 million cells from seven independent datasets including conventional flow cytometry, spectral flow cytometry and mass cytometry. We found that tree-based classifiers and in particular Decision Trees, outperformed other approaches in classification accuracy, speed and memory use. High accuracy was achieved even for cell populations rarer than 1% using decision trees. We validated our decision tree-based approach in a clinical setting using diagnostic blood T cell phenotyping of 107 patients. Automatic quantification of CD4 helper T cell phenotypes achieved 99 % accuracy compared to manual expert assessment. Finally, we combined automated data transformation, supervised and unsupervised gating, an application program interface and a user-friendly desktop-application into FACSPy and FACSPyUI, a fast and scalable open-source toolbox for the analysis and visualization of cytometry data.

bioinformatics↗

bioRxiv2024

A genome-wide association study of mass spectrometry proteomics using the Seer Proteograph platform

Genome-wide association studies (GWAS) with proteomics are essential tools for drug discovery. To date, most studies have used affinity proteomics platforms, which have limited discovery to protein panels covered by the available affinity binders. Furthermore, it is not clear to which extent protein epitope changing variants interfere with the detection of protein quantitative trait loci (pQTLs). Mass spectrometry-based (MS) proteomics can overcome some of these limitations. Here we report a GWAS using the MS-based Seer ProteographTM platform with blood samples from a discovery cohort of 1,260 American participants and a replication in 325 individuals from Asia, with diverse ethnic backgrounds. We analysed 1,980 proteins quantified in at least 80% of the samples, out of 5,753 proteins quantified across the discovery cohort. We identified 252 and replicated 90 pQTLs, where 30 of the replicated pQTLs have not been reported before. We further investigated 200 of the strongest associated cis-pQTLs previously identified using the SOMAscan and the Olink platforms and found that up to one third of the affinity proteomics pQTLs may be affected by epitope effects, while another third were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein expression. The present study demonstrates the complementarity of the different proteomics approaches and reports pQTLs not accessible to affinity proteomics, suggesting that many more pQTLs remain to be discovered using MS-based platforms. Graphical AbstractSummarizing the approach taken to identify potential epitope effects. O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/596028v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@34d11aorg.highwire.dtl.DTLVardef@18c0211org.highwire.dtl.DTLVardef@dbb003org.highwire.dtl.DTLVardef@1009fa7_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Neural speech tracking in newborns: prenatal learning and contributing factors

IntroductionEarly language development in infants is being increasingly studied, though only recently with direct measurements of brain activity rather than with behavioral or physiological measurements. In the current study, we use electroencephalographic (EEG) recordings of 2-week-old infants to look for signs of prenatal learning and to investigate newborns abilities to process language. We also look at the influence of prenatal stress factors and at the predictive value of the newborns language processing abilities for later language development. MethodsSixty pregnant women played a rhyme to their abdomen twice a day from the 34th week of pregnancy until birth, to familiarize the fetus with the rhyme. At around 2 weeks after delivery (mean age 16 days), the newborns were exposed to the familiar rhyme as well as to an unfamiliar one while their EEG was recorded. Additionally, three manipulations of the familiar rhyme were played: (1) low-pass filtered, (2) with changed rhythm, and (3) inverted and played backwards. The data was analyzed to see how well the infant brain signal followed the speech envelope in each condition. Accounting for the heterogenous approach used for neural speech tracking in the literature, we used four methods, namely: (1) coherence, (2) Hilbert coherence, (3) temporal response functions (TRF), and (4) mutual information (MI). The maternal prenatal depression was evaluated with Edinburgh Prenatal Depression Score and the chronic fetal stress was measured from the hair cortisol levels of the 2 week-olds. The language development at 6 months of age was evaluated with the Bayley Scales. Results and discussionOverall, the results indicate the presence of prenatal learning, with the unfamiliar rhyme eliciting stronger cortical tracking (higher coherence and MI) than the familiar rhyme, which suggests stronger brain-to-speech coupling for the unfamiliar rhyme, perhaps deriving from more effort to process the unexpected stimulus. However, the original version of the familiar rhyme proved to be the easiest to track compared to the language- and rhythm-manipulations, (higher MI for the original rhyme than the language manipulation and higher coherence and mTRF correlation coefficients for the original rhyme than the rhythm manipulation). This indicates language discrimination and a prosodic-based learning of the familiar rhyme. Furthermore, there is an indication of phonotactic sensitivity at this young age, with less tracking (lower Hilbert coherence and lower mTRF correlation coefficients) of the low-pass filtered rhyme than the original version, indicating that the phonological cues erased by the filtering were important for the newborns ability to follow the rhyme. Furthermore, the mothers depression scores positively correlated with the infants tracking ability for the familiar rhyme. This suggests that a slightly lower mood was more stimulative for the fetal language development. The chronic fetal stress levels, however, were negatively correlated with the cortical tracking abilities. Importantly, the newborns cortical tracking was positively correlated with the infants language development at 6 months of age, underlining the predictive value of the early assessment of language processing. ConclusionPrenatal learning is well established, but evidence including (healthy) brain data in the first weeks of life is scarce. The current study shows that newborns can discriminate between a familiar and unfamiliar rhyme, while also highlighting the role of prosody in early language processing, and bringing new evidence of their sensitivity to phonotactic cues in auditory stimuli. Furthermore, the newborns ability to track a rhyme is correlated with their language development at 6 months. The newborns cortical tracking of the familiar rhyme is further increased by moderately low maternal mood, but decreased by fetal stress. Future studies with similar fine-grained linguistic designs but of older infants should teach us the timeline of what exactly is learned prenatally and at very early age in respect to language.

developmental biology↗

bioRxiv2023

SARS-CoV-2 spike glycosylation affects function and neutralization sensitivity

The glycosylation of viral envelope proteins can play important roles in virus biology and immune evasion. The spike (S) glycoprotein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) includes 22 N-linked glycosylation sequons and 17 O-linked glycosites. Here, we investigated the effect of individual glycosylation sites on SARS-CoV-2 S function in pseudotyped virus infection assays and on sensitivity to monoclonal and polyclonal neutralizing antibodies. In most cases, removal of individual glycosylation sites decreased the infectiousness of the pseudotyped virus. For glycosylation mutants in the N-terminal domain (NTD) and the receptor binding domain (RBD), reduction in pseudotype infectivity was predicted by a commensurate reduction in the level of virion-incorporated spike protein. Notably, the presence of a glycan at position N343 within the RBD had diverse effects on neutralization by RBD-specific monoclonal antibodies (mAbs) cloned from convalescent individuals. The N343 glycan reduced overall sensitivity to polyclonal antibodies in plasma from COVID-19 convalescent individuals, suggesting a role for SARS-CoV-2 spike glycosylation in immune evasion. However, vaccination of convalescent individuals produced neutralizing activity that was resilient to the inhibitory effect of the N343 glycan.

microbiology↗

bioRxiv2023

Prediction tendency, eye movements, and attention in a unified framework of neural speech tracking

Auditory speech comprehension is a multi-faceted process in which attention, prediction, and sensorimotor integration (via active sensing) interact with or complement each other. Although different conceptual models that focus on one of these aspects exist, we still lack a unified understanding of their role in speech processing. Here, we first replicated two recently published studies from our lab, confirming 1) a positive relationship between individual prediction tendencies and neural speech tracking, and 2) the phenomenon of ocular speech tracking - the tracking of attended speech by eye movements - and its shared contribution with neural activity to speech processing. In addition, we extended these findings with complementary analyses and investigated these phenomena in relation to each other in a multi-speaker paradigm with continuous, narrative speech. Importantly, prediction tendency and ocular speech tracking seem to be unrelated. In contrast to the shared contributions of oculomotor and neural activity to speech processing over a distributed set of brain regions that are critical for attention, individual prediction tendency and its relation to neural speech tracking seem to be largely independent of attention. Based on these findings, we propose a framework that aims to bridge the gaps between attention, prediction, and active (ocular) sensing in order to contribute to a holistic understanding of neural speech processing. In this speculative framework for listening, auditory inflow is, on a basic level, temporally modulated via active ocular sensing, and incoming information is interpreted based on probabilistic assumptions.

neuroscience↗

bioRxiv2023

A synthetic delivery vector for mucosal vaccination

The success of mRNA-based vaccines during the Covid-19 pandemic has highlighted the value of this new platform for vaccine development against infectious disease. However, the CD8+ T cell response remains modest with mRNA vaccines, and these do not induce mucosal immunity, which would be needed to prevent viral spread in the healthy population. To address this drawback, we developed a dendritic cell targeting mucosal vaccination vector, the homopentameric STxB. Here, we describe the highly efficient chemical synthesis of the protein, and its in vitro folding. This straightforward preparation led to a synthetic delivery tool whose biophysical and intracellular trafficking characteristics were largely indistinguishable from recombinant STxB. The chemical approach allowed for the generation of new variants with bioorthogonal handles. Selected variants were chemically coupled to several types of antigens derived from the mucosal viruses SARS-CoV-2 and type 16 human papillomavirus. Upon intranasal administration in mice, mucosal immunity, including resident memory CD8+ T cells and IgA antibodies was induced against these antigens. Our study thereby identifies a novel synthetic antigen delivery tool for mucosal vaccination with an unmatched potential to respond to an urgent medical need.

biochemistry↗

bioRxiv2023

Nanoparticle Enrichment Mass-Spectrometry Proteomics Identifies Protein Altering Variants for Precise pQTL Mapping

Genome-wide association studies (GWAS) with proteomics generate hypotheses on protein function and offer genetic evidence for drug target prioritization. Although most protein quantitative loci (pQTLs) have so far been identified by high-throughput affinity proteomics platforms, these methods also have some limitations, such as uncertainty about target identity, non-specific binding of aptamers, and inability to handle epitope-modifying variants that affect affinity binding. Mass spectrometry (MS) proteomics has the potential to overcome these challenges and broaden the scope of pQTL studies. Here, we employ the recently developed MS-based Proteograph workflow (Seer, Inc.) to quantify over 18,000 unique peptides from almost 3,000 proteins in more than 320 blood samples from a multi-ethnic cohort. We implement a bottom-up MS-proteomics approach for the detection and quantification of blood-circulating proteins in the presence of protein altering variants (PAVs). We identify 184 PAVs located in 137 genes that are significantly associated with their corresponding variant peptides in MS data (MS-PAVs). Half of these MS-PAVs (94) overlap with cis-pQTLs previously identified by affinity proteomics pQTL studies, thus confirming the target specificity of the affinity binders. An additional 54 MS-PAVs overlap with trans-pQTLs (and not cis-pQTLs) in affinity proteomics studies, thus identifying the putatively causal cis-encoded protein and providing experimental evidence for its presence in blood. The remaining 36 MS-PAVs have not been previously reported and include proteins that may be inaccessible to affinity proteomics, such as a variant in the incretin pro-peptide (GIP) that associates with type 2 diabetes and cardiovascular disease. Overall, our study introduces a novel approach for analyzing MS-based proteomics data within the GWAS context, provides new insights relevant to genetics-based drug discovery, and highlights the potential of MS-proteomics technologies when applied at population scale. HighlightsO_LIThis is the first pQTL study that uses the Proteograph (Seer Inc.) mass spectrometry-based proteomics workflow. C_LIO_LIWe introduce a novel bottom-up proteomics approach that accounts for protein altering variants in the detection of pQTLs. C_LIO_LIWe confirm the target and potential epitope effects of affinity binders for cis-pQTLs from affinity proteomics studies. C_LIO_LIWe establish putatively causal proteins for known affinity proteomics trans-pQTLs and confirm their presence in blood. C_LIO_LIWe identify novel protein altering variants in proteins of clinical relevance that may not be accessible to affinity proteomics. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/537640v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@5db14forg.highwire.dtl.DTLVardef@123c1edorg.highwire.dtl.DTLVardef@90ebb6org.highwire.dtl.DTLVardef@6320ff_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2023

Eye movements track prioritized auditory features in selective attention to natural speech

Over the last decades, cognitive neuroscience has identified a distributed set of brain regions that are critical for attention - one of the key principles of adaptive behavior. A strong anatomical overlap with brain regions critical for oculomotor processes suggests a joint network for attention and eye movements. However, the role of this shared network in complex, naturalistic environments remains understudied. Here, we investigated eye movements in relation to (un)attended sentences of natural speech in simultaneously recorded eye tracking and magnetoencephalographic (MEG) data. Using temporal response functions (TRF), we show that eye gaze tracks acoustic features (envelope and acoustic onsets) of attended speech, a phenomenon we termed ocular speech tracking. Ocular speech envelope tracking even differentiates a target from a distractor in a multi speaker context and is further related to intelligibility. Moreover, we provide evidence for its contribution to neural differences in speech processing, emphasizing the necessity to consider oculomotor activity in future research and in the interpretation of neural differences in auditory cognition. Our results extend previous findings of a joint network of attention and eye movement control as well as motor theories of speech. They provide valuable new directions for research into the neurobiological mechanisms of the phenomenon, its dependence on learning and plasticity, and its functional implications in social communication.

neuroscience↗

bioRxiv2023

The statistics of natural shapes predict high-level aftereffects in human vision

Shape perception is essential for numerous everyday behaviors from object recognition to grasping and handling objects. Yet how the brain encodes shape remains poorly understood. Here, we probed shape representations using visual aftereffects--perceptual distortions that occur following extended exposure to a stimulus--to resolve a long-standing debate about shape encoding. We implemented contrasting low-level and high-level computational models of neural adaptation, which made precise and distinct predictions about the illusory shape distortions the observers experience following adaptation. Directly pitting the predictions of the two models against one another revealed that the perceptual distortions are driven by high-level shape attributes derived from the statistics of natural shapes. Our findings suggest that the diverse shape attributes thought to underlie shape encoding (e.g., curvature distributions, skeletons, aspect ratio) are the result of a visual system that learns to encode natural shape geometries based on observing many objects.

neuroscience↗

bioRxiv2022

Age-related changes in 'cortical' 1/f dynamics are explained by cardiac activity

The power of electrophysiologically measured cortical activity decays with an approximately 1/fX function. The slope of this decay (i.e. the spectral exponent, X) is modulated by various factors such as age, cognitive states or psychiatric/neurological disorders. Interestingly, a mostly parallel line of research has also uncovered similar effects for the spectral slope in the electrocardiogram (ECG). This raises the question whether these bodywide changes in spectral slopes are (in-)dependent. Focusing on well-established age-related changes in spectral slopes we analyzed a total of 1282 recordings of magnetoencephalography (MEG) resting state measurements with concurrent ECG in an age-diverse sample (18-88 years). Using a diverse array of analytical approaches, we demonstrate that the aperiodic signal recorded via surface electrodes/sensors originates from multiple physiological sources. Furthermore, our results suggest that common "artifact" rejection approaches (i.e. ICA) may not be sufficient to separate cardiac from neural activity. In particular, significant parts of age-related changes in aperiodic activity normally interpreted to be of neural origin can be explained by cardiac activity. Moreover, our results suggest that changes (flattening/steepening) of the spectral slope with age are dependent on the recording site and investigated frequency range. Our results highlight the complexity of aperiodic activity while raising concerns when interpreting aperiodic activity as "cortical" without considering physiological influences.

neuroscience↗

bioRxiv2022

TF-Prioritizer: a java pipeline to prioritize condition-specific transcription factors

BackgroundEukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results. ResultsWe developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences. ConclusionTF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.

bioinformatics↗

bioRxiv2022

Epistasis lowers the genetic barrier to SARS-CoV-2 neutralizing antibody escape

Consecutive waves of SARS-CoV-2 infection have been driven in part by the repeated emergence of variants with mutations that confer resistance to neutralizing antibodies Nevertheless, prolonged or repeated antigen exposure generates diverse memory B-cells that can produce affinity matured receptor binding domain (RBD)-specific antibodies that likely contribute to ongoing protection against severe disease. To determine how SARS-CoV-2 omicron variants might escape these broadly neutralizing antibodies, we subjected chimeric viruses encoding spike proteins from ancestral, BA.1 or BA.2 variants to selection pressure by a collection of 40 broadly neutralizing antibodies from individuals with various SARS-CoV-2 antigen exposures. Notably, pre-existing substitutions in the BA.1 and BA.2 spikes facilitated acquisition of resistance to many broadly neutralizing antibodies. Specifically, selection experiments identified numerous RBD substitutions that did not confer resistance to broadly neutralizing antibodies in the context of the ancestral Wuhan-Hu-1 spike sequence, but did so in the context of BA.1 and BA.2. A subset of these substitutions corresponds to those that have appeared in several BA.2 daughter lineages that have recently emerged, such as BA.5. By including as few as 2 or 3 of these additional changes in the context of BA.5, we generated spike proteins that were resistant to nearly all of the 40 broadly neutralizing antibodies and were poorly neutralized by plasma from most individuals. The emergence of omicron variants has therefore not only allowed SARS-CoV-2 escape from previously elicited neutralizing antibodies but also lowered the genetic barrier to the acquisition of resistance to the subset of antibodies that remained effective against early omicron variants.

microbiology↗

bioRxiv2022

Memory B cell responses to Omicron subvariants after SARS-CoV-2 mRNA breakthrough infection

Individuals that receive a 3rd mRNA vaccine dose show enhanced protection against severe COVID19 but little is known about the impact of breakthrough infections on memory responses. Here, we examine the memory antibodies that develop after a 3rd or 4th antigenic exposure by Delta or Omicron BA.1 infection, respectively. A 3rd exposure to antigen by Delta breakthrough increases the number of memory B cells that produce antibodies with comparable potency and breadth to a 3rd mRNA vaccine dose. A 4th antigenic exposure with Omicron BA.1 infection increased variant specific plasma antibody and memory B cell responses. However, the 4th exposure did not increase the overall frequency of memory B cells or their general potency or breadth compared to a 3rd mRNA vaccine dose. In conclusion, a 3rd antigenic exposure by Delta infection elicits strain-specific memory responses and increases in the overall potency and breadth of the memory B cells. In contrast, the effects of a 4th antigenic exposure with Omicron BA.1 is limited to increased strain specific memory with little effect on the potency or breadth of memory B cell antibodies. The results suggest that the effect of strain-specific boosting on memory B cell compartment may be limited.

immunology↗

bioRxiv2022

Speech intelligibility changes the temporal evolution of neural speech tracking

Listening to speech with poor signal quality is challenging. Neural speech tracking of degraded speech has been used to advance the understanding of how brain processes and speech intelligibility are interrelated, however the temporal dynamics of neural speech tracking are not clear. In the present MEG study, we thereby exploited temporal response functions (TRFs) and generated signal-degraded speech to depict the temporal evolution of speech intelligibility modulation on neural speech tracking. In addition, we inter-related facets of neural speech tracking (e.g., speech envelope reconstruction, speech-brain coherence, and components of broadband coherence spectra) to endorse our findings in TRFs. Our TRF analysis yielded marked temporally differential effects of vocoding: reduction of intelligibility went along with large increases of early peak responses ([~]50-110 ms, M50TRF), but strongly reduced responses around 175-230 ms (M200TRF). For the late responses 315-380 ms (M350TRF), the maximum response occurred for degraded speech that was still comprehensible then declined with reduced intelligibility. Furthermore, we related the TRF components to our other neural "tracking" measures and found that M50TRF and M200TRF play a differential role in the shifting center frequency of the broadband coherence spectra. Overall, our study highlights the importance of time-resolved computation and parametrization of coherence spectra on neural speech tracking and provides a better understanding of degraded speech processing. HighlightsO_LIWe use MEG to show that speech intelligibility differentially impacts the temporal evolution of neural speech tracking. C_LIO_LITRF responses around 200 ms show the strongest relationship with behaviour. C_LIO_LIRelating TRF effects to parameterized coherence spectra using FOOOF suggests that M50TRF and M200TRF reflect shifts in which speech features are tracked over time. C_LI

neuroscience↗

bioRxiv2022

Re-direction of phagosomes to the recycling expulsion pathway by a fungal pathogen

The analysis of host-pathogen interactions bears the potential to discover novel pathogenicity mechanisms and to obtain novel insights into basic mechanisms of cell biology. Here, we obtained unprecedented insight into both. We discovered that the HscA protein on the conidial surface of the clinically important human-pathogenic fungus Aspergillus fumigatus acts as an effector protein. It inhibits phagosome maturation and reprograms phagosomes for expulsion of conidia. HscA anchors the human p11 protein to phagosomes. p11 is a decisive factor for targeting phagosomes either to the degradative or secretory pathway. The relevance of our findings is indicated by the identification of an SNP in the non-coding region of the human p11 gene that affects its translation and is associated with heightened susceptibility to invasive pulmonary aspergillosis.

cell biology↗