[A mathematical model to estimate the number of unreported SARS-CoV-2 infections in the early phase of the pandemic using Germany and Italy as examples]. / Ein mathematisches Modell zur Schätzung der Dunkelziffer von SARS-CoV-2-Infektionen in der Frühphase der Pandemie am Beispiel Deutschland und Italien.

BACKGROUND: Especially in the early phase, it is difficult to obtain reliable figures on the spread of a pandemic. The effects of the COVID-19 pandemic and the associated comprehensive but incomplete data monitoring provide a strong reason to estimate the number of unreported cases. AIM: The aim of this paper is to present a simple mathematical model that allows early estimation of the number of unregistered cases (underreporting). MATERIAL AND METHODS: Prevalences of reported infections in different age groups are combined with additional assumptions on relative contact rates. From this, a corrected prevalence is derived for each age group, which can then be used to estimate the number of unreported cases. RESULTS: Our model derives for Germany in mid-April 2020 about 2.8 times more total infections than registered cases. For Italy, the model results in a factor of 8.3. The case mortalities derived from this are 0.98% for Germany and 1.51% for Italy, which are much closer together than the case mortalities of 2.7% and 12.6% derived purely from the number of reports available at that time. CONCLUSION: The number of unreported SARS-CoV-2-infected cases derived from the model can largely explain the difference in observations in case mortalities and of conditions in the early phase of the COVID-19 pandemic in Germany and Italy. The model is simple, fast, and robust to implement, and can respond well when the reporting numbers are not representative of the population in terms of age structure. We suggest considering this model for efficient and early estimations of unreported case numbers in future epidemics and pandemics.

Poor transcript-protein correlation in the brain: negatively correlating gene products reveal neuronal polarity as a potential cause.

Transcription, translation, and turnover of transcripts and proteins are essential for cellular function. The contribution of those factors to protein levels is under debate, as transcript levels and cognate protein levels do not necessarily correlate due to regulation of translation and protein turnover. Here we propose neuronal polarity as a third factor that is particularly evident in the CNS, leading to considerable distances between somata and axon terminals. Consequently, transcript levels may negatively correlate with cognate protein levels in CNS regions, i.e., transcript and protein levels behave reciprocally. To test this hypothesis, we performed an integrative inter-omics study and analyzed three interconnected rat auditory brainstem regions (cochlear nuclear complex, CN; superior olivary complex, SOC; inferior colliculus, IC) and the rest of the brain as a reference. We obtained transcript and protein sets in these regions of interest (ROIs) by DNA microarrays and label-free mass spectrometry, and performed principal component and correlation analyses. We found 508 transcript|protein pairs and detected poor to moderate transcript|protein correlation in all ROIs, as evidenced by coefficients of determination from 0.34 to 0.54. We identified 57-80 negatively correlating gene products in the ROIs and intensively analyzed four of them for which the correlation was poorest. Three cognate proteins (Slc6a11, Syngr1, Tppp) were synaptic and hence candidates for a negative correlation because of protein transport into axon terminals. Thus, we systematically analyzed the negatively correlating gene products. Gene ontology analyses revealed overrepresented transport/synapse-related proteins, supporting our hypothesis. We present 30 synapse/transport-related proteins with poor transcript|protein correlation. In conclusion, our analyses support that protein transport in polar cells is a third factor that influences the protein level and, thereby, the transcript|protein correlation. OPEN SCIENCE BADGES: This article has received a badge for *Open Materials* and *Open Data* because it provided all relevant information to reproduce the study in the manuscript and because it made the data publicly available. The data can be accessed at https://osf.io/ha28n/. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/.

Tubulin or Not Tubulin: Heading Toward Total Protein Staining as Loading Control in Western Blots.

Western blotting is an analytical method widely used for detecting and (semi-)quantifying specific proteins in given samples. Western blots are continuously applied and developed by the protein community. This review article focuses on a significant, but not yet well-established, improvement concerning the internal loading control as a prerequisite to accurately quantifying Western blots. Currently, housekeeping proteins (HKPs) like actin, tubulin, or GAPDH are often used to check for equal loading or to compensate potential loading differences. However, this loading control has multiple drawbacks. Staining of the total protein on the blotting membrane has emerged as a better loading control. Total protein staining (TPS) represents the actual loading amount more accurately than HKPs due to minor technical and biological variation. Further, the broad dynamic range of TPS solves the issue of HKPs that commonly fail to show loading differences above small loading amounts of 0.5-10 µg. Although these and further significant advantages have been demonstrated over the past 10 years, only a small percentage of laboratories take advantage of it. The objective of this review article is to collect and compare information about TPS options and to invite users to reconsider their applied loading control. Nine benefits of TPS are discussed and seven different variants are critically evaluated by comparing technical details. Consequently, this review article offers an orientation in selecting the appropriate staining type. I conclude that TPS should be the preferred loading control in future Western blot approaches.

Neuroproteomics in the auditory brainstem: candidate proteins for ultrafast and precise information processing.

In the mammalian auditory brainstem, the cochlear nuclear complex (CN) and the superior olivary complex (SOC) feature structural and functional specializations for ultrafast (<1 ms) and precise information processing. Their proteome, the basis for structure and function, has been rarely analyzed so far. Here we identified and quantified the protein profiles of three major auditory brainstem regions of adult rats, the CN, the SOC, and the inferior colliculus (IC). The rest of the brain served as a reference. Via label-free quantitative mass spectrometry and 2-D DIGE/MALDI-MS, we identified 584 and 297 proteins in the plasma membrane/synaptic vesicle proteome and the cytosolic proteome, respectively. 'Region-typical' proteins, i.e., those with higher abundance in one region than in the other three, were considered candidates for functional specializations. Key proteins were validated via Western blots and immunohistochemistry. Functional annotation clustering revealed an overrepresentation of neurofilament proteins among the CN+SOC-typical proteins. These are related to regulation of axon diameter and, thereby, conduction velocity. Interestingly, the sets of synapse-associated proteins differed between regions. For example, synaptotagmin-2 (Syt2), a Ca2+ sensor for fast exocytosis, was CN+SOC+IC-typical, whereas Syt1 was CN+SOC+IC-atypical. Together, our quantitative comparison of protein profiles has revealed several interesting candidate proteins for ultrafast and precise information processing.

Epicocconone staining: a powerful loading control for Western blots.

Western blot analysis is routinely employed for quantifying differences in protein levels between samples. To control equal loading and to arithmetically compensate loading differences, immunodetection of housekeeping proteins is commonly used. Due to potential biases, this approach has been criticized. Here, we evaluate epicocconone-based total protein staining (E-ToPS) as an alternative. We compared it with two other total protein stainings (Coomassie and Sypro Ruby) and with immunodetection of housekeeping proteins (ß-tubulin and glyceraldehyde 3-phosphate dehydrogenase). Evaluation comprised both the natural and the synthetic epicocconone compound. Both compounds produced highly congruent results and showed more sensitive (≤ 1 µg) and less variable staining properties than the other variants. The high sensitivity of E-ToPS, covering minute protein amounts, makes it a powerful loading control, especially for precious samples. Regarding biological and technical variances, E-ToPS outperformed immunostaining against ß-tubulin and glyceraldehyde 3-phosphate dehydrogenase. Furthermore, E-ToPS had no impact on subsequent immunodetection, allowing for an early control of proper loading prior to immunodetection. In contrast to earlier studies, we found logarithmic staining properties for E-ToPS, which should be considered when using it for arithmetic normalization. In conclusion, we demonstrate the superior power of E-ToPS as a loading control for Western blots.

Anti-AGO1 Antibodies Identify a Subset of Autoimmune Sensory Neuronopathy.

BACKGROUND AND OBJECTIVES: Autoantibodies (Abs) improve diagnosis and treatment decisions of idiopathic neurologic disorders. Recently, we identified Abs against Argonaute (AGO) proteins as potential autoimmunity biomarkers in neurologic disorders. In this study, we aim to reveal (1) the frequency of AGO1 Abs in sensory neuronopathy (SNN), (2) titers and IgG subclasses, and (3) their clinical pattern including response to treatment. METHODS: This retrospective multicentric case/control study screened 132 patients with SNN, 301 with non-SNN neuropathies, 274 with autoimmune diseases (AIDs), and 116 healthy controls (HCs) for AGO1 Abs through ELISA. Seropositive cases were also tested for IgG subclasses, titers, and conformation specificity. RESULTS: AGO1 Abs occurred in 44 patients, comprising significantly more of those with SNN (17/132 [12.9%]) than those with non-SNN neuropathies (11/301 [3.7%]; p = 0.001), those with AIDs (16/274 [5.8%]; p = 0.02), or HCs (0/116; p < 0.0001). Ab titers ranged from 1:100 to 1:100,000. IgG subclass was mainly IgG1, and 11/17 AGO1 Ab-positive SNN (65%) had a conformational epitope. AGO1 Ab-positive SNN was more severe than AGO1 Ab-negative SNN (e.g., SNN score: 12.2 vs 11.0, p = 0.004), and they more frequently and more efficiently responded to immunomodulatory treatments than AGO1 Ab-negative SNN (7/13 [54%] vs 6/37 [16%], p = 0.02). Regarding the type of treatments more precisely, this significant difference was confirmed for the use of IV immunoglobulins (IVIg) but not for steroids or second-line treatments. Multivariate logistic regression adjusted for potential confounders showed that AGO1 Ab positivity was the only predictor of response to treatment (OR 4.93, 1.10-22.24 95% CI, p = 0.03). DISCUSSION: Although AGO Abs are not specific for SNN, based on our retrospective data, they may identify a subset of cases with SNN with more severe features and a possibly better response to IVIg. The significance of AGO1 Abs in clinical practice needs to be explored on a larger series.

Conformation-stabilizing ELISA and cell-based assays reveal patient subgroups targeting three different epitopes of AGO1 antibodies.

Autoantibodies (Abs) are biomarkers for many disease conditions and are increasingly used to facilitate diagnosis and treatment decisions. To guarantee high sensitivity and specificity, the choice of their detection method is crucial. Via cell-based assays, we recently found 21 patients with neurological diseases positive for antibodies against argonaute (AGO), 10 of which having a neuropathy (NP). Here, we established a simple and conformation-sensitive ELISA with the aim to distinguish between AGO1 Abs against conformational epitopes and non-conformational epitopes and to reveal further characteristics of AGO1 antibodies in NP and autoimmune disease (AID). In a retrospective multicenter case/control and observational study, we tested 434 patients with NP, 274 disease controls with AID, and 116 healthy controls (HC) for AGO1 Abs via conformation-stabilizing ELISA. Seropositive patients were also tested for conformation-specificity via comparative denaturing/stabilizing ELISA (CODES-ELISA), CBA positivity, AGO1 titers and IgG subclasses, and AGO2 reactivity. These parameters were statistically compared among different epitope-specific patient groups. We found Abs in 44 patients, including 28/434 (6.5%) NP, 16/274 (5.8%) AID, and 0/116 (0%) HC. Serum reactivity was consistently higher for AGO1 than AGO2. Globally among the 44 AGO1 Abs-positive patients, 42 were also tested in CBA for AGO1 Abs positivity and 15 (35.7%) were positive. Furthermore, 43 were tested for conformation-specificity and 32 (74.4%) bound a conformational epitope. Among the subgroups of highly positive patients (ELISA z-score >14) with sera binding conformational epitopes (n=23), 14 patient sera were also CBA positive and 9 bound a second conformational but CBA-inaccessible epitope. A third, non-conformational epitope was bound by 11/43 (15.6%). Among the epitope-specific patient subgroups, we found significant differences regarding the Abs titers, IgG subclass, and AGO2 reactivity. When comparing AGO1 Abs-positive NP versus AID patients, we found the conformation-specific and CBA inaccessible epitope significantly more frequently in AID patients. We conclude that 1) conformational ELISA was more sensitive than CBA in detecting AGO1 Abs, 2) serum reactivity is higher for AGO1 than for AGO2 at least for NP patients, 3) AGO1 Abs might be a marker-of-interest in 6.5% of NP patients, 4) distinguishing epitopes might help finding different patient subgroups.

CIDP Antibodies Target Junction Proteins and Identify Patient Subgroups: An Autoantigenomic Approach.

OBJECTIVE: To discover systemic characteristics in the repertoires of targeted autoantigens in chronic inflammatory demyelinating polyneuropathy (CIDP), we detected the entire autoantigen repertoire of patients and controls and analyzed them systematically. METHODS: We screened 43 human serum samples, of which 22 were from patients with CIDP, 12 from patients with other neuropathies, and 9 from healthy controls via HuProt Human Proteome microarrays testing about 16,000 distinct human bait proteins. Autoantigen repertoires were analyzed via bioinformatical autoantigenomic approaches: principal component analysis, analysis of the repertoire sizes in disease groups and clinical subgroups, and overrepresentation analyses using Gene Ontology and PantherDB. RESULTS: The autoantigen repertoires enabled the identification of a subgroup of 10/22 patients with CIDP with a younger age at onset and a higher frequency of mixed motor and sensory CIDP. IV immunoglobulin therapy responders targeted 3 times more autoantigens than nonresponders. No CIDP-specific autoantibody is present in all patients; however, anchoring junction components were significantly targeted by 86.4% of patients with CIDP. There are potential novel CIDP-specific autoantigens such as the myelination- or axo-glial structure-related proteins actin-related protein 2/3 complex subunit 1B, band 4.1-like protein 2, cadherin-15, cytohesin-1, epidermal growth factor receptor, ezrin, and radixin. CONCLUSIONS: The repertoire of targeted autoantigens of patients with CIDP differs in a systematic degree from those of controls. Systematic autoantigenomic approaches can help to understand the disease and to discover novel bioinformatical tools and novel autoantigen panels to improve diagnosis, treatment, prognosis, or patient stratification.

Proper definition of the set of autoantibody-targeted antigens relies on appropriate reference group selection.

Autoimmune diseases are frequently associated with autoantibodies. Recently, large sets of autoantibody-targeted antigens ("autoantigen-omes") of patient and control sera have been revealed, enabling autoantigen-omic approaches. However, statistical standards for defining such autoantigen-omes are lacking. The z-score indicates how many standard deviations an antigen reactivity of a given sample is from the mean reactivity of the corresponding antigen in a reference group. Hence, it is a common measure to define significantly positive reactivity in autoantigen profiling approaches. Here, we address the risk of biased analyses resulting from unbalanced selection of the reference group. Three study groups were selected. Patients-of-interest were chronic inflammatory demyelinating polyneuropathy (CIDP); controls were other neuropathies (ONP); and healthy controls (HC). Each serum was screened for significant autoantigen reactivity using HuProt™ protein arrays. We compared three possible selections of reference groups for statistical z-score calculations: method#1, the control groups (ONP + HC); method #2, all groups together; method #3, the respective other groups (e.g., CIDP + HC for the ONP autoantigen-ome). The method selection seriously affected the size of the autoantigen-omes. Method #1 introduced a bias favoring significantly more antigens per patient in the CIDP group (for z >4: 19 ±â€¯3 antigens) than in the control groups (ONP: 2 ±â€¯1; HC: 0 ±â€¯0). The more balanced methods #2 and #3 did not result in significant differences. This contribution may help to avoid interpretation biases and to develop guidelines for population studies revealing autoantigen-omes via high throughput studies such as protein microarrays, immunoprecipitation with mass spectrometry, or phage display assays.

Anti-FGFR3 antibody epitopes are functional sites and correlate with the neuropathy pattern.

Antibodies against FGFR3 define a subgroup of sensory neuropathy (SN). The aim of this study was to identify the epitope(s) of anti-FGFR3 autoantibodies and potential epitope-dependent clinical subtypes. Using SPOT methodology, five specific candidate epitopes, three in the juxtamembrane domain (JMD) and two in the tyrosine kinase domain (TKD), were screened with 68 anti-FGFR3-positive patients and 35 healthy controls. The identified epitopes cover 6/15 functionally relevant sites of the protein. Four patients reacted with the JMD and 11 with the TKD, partly even in a phosphorylation-state dependent manner. The epitope could not be identified in the others. Patients with antibodies recognizing TKD exhibited a more severe clinical and electrophysiological impairment than others.

Argonaute Autoantibodies as Biomarkers in Autoimmune Neurologic Diseases.

OBJECTIVE: To identify and characterize autoantibodies (Abs) as novel biomarkers for an autoimmune context in patients with central and peripheral neurologic diseases. METHODS: Two distinct approaches (immunoprecipitation/mass spectrometry-based proteomics and protein microarrays) and patients' sera and CSF were used. The specificity of the identified target was confirmed by cell-based assay (CBA) in 856 control samples. RESULTS: Using the 2 methods as well as sera and CSF of patients with central and peripheral neurologic involvement, we identified Abs against the family of Argonaute proteins (mainly AGO1 and AGO2), which were already reported in systemic autoimmunity. AGO-Abs were mostly of immunoglobulin G 1 subclass and conformation dependent. Using CBA, AGO-Abs were detected in 21 patients with a high suspicion of autoimmune neurologic diseases (71.4% were women; median age 57 years) and only in 4/856 (0.5%) controls analyzed by CBA (1 diagnosed with small-cell lung cancer and the other 3 with Sjögren syndrome). Among the 21 neurologic patients identified, the main clinical presentations were sensory neuronopathy (8/21, 38.1%) and limbic encephalitis (6/21, 28.6%). Fourteen patients (66.7%) had autoimmune comorbidities and/or co-occurring Abs, whereas AGO-Abs were the only autoimmune biomarker for the remaining 7/21 (33.3%). Thirteen (61.9%) patients were treated with immunotherapy; 8/13 (61.5%) improved, and 3/13 (23.1%) remained stable, suggesting an efficacy of these treatments. CONCLUSIONS: AGO-Abs might be potential biomarkers of autoimmunity in patients with central and peripheral nonparaneoplastic neurologic diseases. In 7 patients, AGO-Abs were the only biomarkers; thus, their identification may be useful to suspect the autoimmune character of the neurologic disorder. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that AGO-Abs are more frequent in patients with autoimmune neurologic diseases than controls.

40 years Western blotting: A scientific birthday toast.

The Western blot technique was first published 40 years ago. Since then, it has been mentioned in the titles, abstracts, and keywords of more than 400,000 PubMed-listed publications. This anniversary represents an opportunity to look back to its origins, to address the question as to whether the technique is outdated and heading toward being replaced, and to point out current improvements. Publications within the last ten years indicate Western blotting may be the most used protein-analytical technique. Although no decline in its usage is visible, the method has been moving out of the spotlight.

Autoantigenomics: Holistic characterization of autoantigen repertoires for a better understanding of autoimmune diseases.

Autoimmune diseases are mostly characterized by autoantibodies in the patients' serum or cerebrospinal fluid, representing diagnostic or prognostic biomarkers. For decades, research has focused on single autoantigens or panels of single autoantigens. In this article, we advocate to broaden the focus by addressing the entire autoantigen repertoire in a systemic "omics-like" way. This approach aims to capture the enormous biodiversity in the sets of targeted antigens and pave the way toward a more holistic understanding of the concerted character of antibody-related humoral immune responses. Ongoing technological progress permits high-throughput screenings of thousands of autoantigens in parallel, e.g., via protein microarrays, phage display, or immunoprecipitation with mass spectrometry. We argue that the time is right for combining omics and autoantibody screening approaches into "autoantigenomics" as a novel omics subcategory. In this article, we introduce the concept of autoantigenomics, describe its roots and application options, and demarcate the method from related holistic approaches such as systems serology or immune-related transcriptomics and proteomics. We suggest the following extendable method set to be applied to autoantigen repertoires: (1) principal component analysis, (2) hierarchical cluster analysis, (3) partial least-square discriminant analysis or orthogonal projections to latent structures discriminant analysis, (4) analysis of the repertoire sizes in disease groups and clinical subgroups, (5) overrepresentation analyses using databases like those of Gene Ontology, Reactome Pathway, or DisGeNET, (6) analysis of pathways that are significantly targeted by specific repertoires, and (7) machine learning approaches. In an unsupervised way, these methods can identify clusters of autoantigens sharing certain functional or spatial properties, or clusters of patients comprising clinical subgroups potentially useful for patient stratification. In a supervised way, these methods can lead to prediction models that may eventually assist diagnosis and prognosis. The untargeted autoantigenomics approach allows for the systematic survey of antibody-related humoral immune responses. This may enhance our understanding of autoimmune diseases in a more comprehensive way compared to current single or panel autoantibodies approaches.

Reducing the risk of misdiagnosis of indirect ELISA by normalizing serum-specific background noise: The example of detecting anti-FGFR3 autoantibodies.

Indirect enzyme-linked immunosorbent assay (ELISA) is an important diagnostic method as it enables the quantification of the presence of autoantibodies in human blood sera. However, unspecific binding of antibodies to the solid phase causes considerable serum-specific background noise (SSBN), involving the risk of false positive diagnosis. Therefore, we present a simple and concise, yet obvious proof-of-principle of a recently suggested normalization method. The method is based on subtracting SSBN by using non-coated ELISA wells as a control for each serum-of-interest. We performed ELISA to quantify anti-fibroblast growth factor receptor 3 (FGFR3) antibody levels in three positive controls (two anti-FGFR3-positive patients and a rabbit antiserum against FGFR3) and 58 negative controls (healthy blood donors). In all subjects, we found considerable unspecific reactivity which strongly varied among subjects. The conventional normalization method was not able to balance this strong SSBN, as demonstrated by 2/58 false positive healthy controls and one FGFR3-positive patient that was hidden in the noise (false negative). SSBN normalization reduced the frequency of false-positives to 0/58. Further, all three anti-FGFR3-positive sera were successfully detected and even doubled their z-score used to determine positivity. Albeit occupying more space on the ELISA plate, we strongly recommend considering this normalization method when working with blood sera. To better put the idea across to the community, we depict the SSBN issue and its solution in a graphic scheme. We conclude that SSBN normalization increases the sensitivity and specificity of indirect ELISA and thereby reduces the risk of false positive and false negative diagnosis. © 2019. Licensed under the Creative Commons [CC BY-NC 4.0 licence, https://doi.org/10.1016/j.jim.2019.01.004].

Completing the Immunological Fingerprint by Refractory Proteins: Autoantibody Screening via an Improved Immunoblotting Technique.

PURPOSE: Identifying autoantigens of serological autoantibodies requires expensive methods, such as protein microarrays or IP+MS. Thus, sera are commonly pre-screened for interesting immunopatterns via immunocytochemistry/immunohistochemistry. However, distinguishing immunopatterns can be difficult and intracellular antigens are less accessible. Therefore, a simple and cheap immunoblot screening able to distinguish immunopatterns and to detect refractory proteins is presented. EXPERIMENTAL DESIGN: Five steps of immunoblotting-based autoantigen screening are revised: (1) choice of protein source, (2) protein extraction, (3) protein separation, (4) protein transfer, (5) antigen detection. Thereafter, 52 patients' sera with chronic inflammatory demyelinating polyneuropathy (CIDP) and 45 controls were screened. RESULTS: The protein source impacts the detected antigen set. Steps 2-4 can be adapted for refractory proteins. Furthermore, longitudinal cutting of protein lanes saves ≥75% of time and material and allows for exact comparison of band patterns. As the latter are individually specific and temporarily constant, we call them "immunological fingerprints". In a proof-of-principle, a 155 kDa immunoband was detected with two anti-neurofascin-155-positive CIDP sera and two further immunobands (120/220 kDa) specific to a subgroup of 3-6 of 52 CIDP patients. CONCLUSIONS AND CLINICAL RELEVANCE: Adapted immunoblotting is a cheap and simple method for accurate serum screening including refractory and intracellular antigens.