Unveiling the proteome-wide autoreactome enables enhanced evaluation of emerging CAR T cell therapies in autoimmunity.

Given the global surge in autoimmune diseases, it is critical to evaluate emerging therapeutic interventions. Despite numerous new targeted immunomodulatory therapies, comprehensive approaches to apply and evaluate the effects of these treatments longitudinally are lacking. Here, we leveraged advances in programmable-phage immunoprecipitation methodology to explore the modulation, or lack thereof, of autoantibody profiles, proteome-wide, in both health and disease. Using a custom set of over 730,000 human-derived peptides, we demonstrated that each individual, regardless of disease state, possesses a distinct and complex constellation of autoreactive antibodies. For each individual, the set of resulting autoreactivites constituted a unique immunological fingerprint, or "autoreactome," that was remarkably stable over years. Using the autoreactome as a primary output, we evaluated the relative effectiveness of various immunomodulatory therapies in altering autoantibody repertoires. We found that therapies targeting B cell maturation antigen (BCMA) profoundly altered an individual's autoreactome, while anti-CD19 and anti-CD20 therapies had minimal effects. These data both confirm that the autoreactome comprises autoantibodies secreted by plasma cells and strongly suggest that BCMA or other plasma cell-targeting therapies may be highly effective in treating currently refractory autoantibody-mediated diseases.

Unveiling the autoreactome: Proteome-wide immunological fingerprints reveal the promise of plasma cell depleting therapy.

The prevalence and burden of autoimmune and autoantibody mediated disease is increasing worldwide, yet most disease etiologies remain unclear. Despite numerous new targeted immunomodulatory therapies, comprehensive approaches to apply and evaluate the effects of these treatments longitudinally are lacking. Here, we leverage advances in programmable-phage immunoprecipitation (PhIP-Seq) methodology to explore the modulation, or lack thereof, of proteome-wide autoantibody profiles in both health and disease. We demonstrate that each individual, regardless of disease state, possesses a distinct set of autoreactivities constituting a unique immunological fingerprint, or "autoreactome", that is remarkably stable over years. In addition to uncovering important new biology, the autoreactome can be used to better evaluate the relative effectiveness of various therapies in altering autoantibody repertoires. We find that therapies targeting B-Cell Maturation Antigen (BCMA) profoundly alter an individual's autoreactome, while anti-CD19 and CD-20 therapies have minimal effects, strongly suggesting a rationale for BCMA or other plasma cell targeted therapies in autoantibody mediated diseases.

Deep profiling of protease substrate specificity enabled by dual random and scanned human proteome substrate phage libraries.

Proteolysis is a major posttranslational regulator of biology inside and outside of cells. Broad identification of optimal cleavage sites and natural substrates of proteases is critical for drug discovery and to understand protease biology. Here, we present a method that employs two genetically encoded substrate phage display libraries coupled with next generation sequencing (SPD-NGS) that allows up to 10,000-fold deeper sequence coverage of the typical six- to eight-residue protease cleavage sites compared to state-of-the-art synthetic peptide libraries or proteomics. We applied SPD-NGS to two classes of proteases, the intracellular caspases, and the ectodomains of the sheddases, ADAMs 10 and 17. The first library (Lib 10AA) allowed us to identify 104 to 105 unique cleavage sites over a 1,000-fold dynamic range of NGS counts and produced consensus and optimal cleavage motifs based position-specific scoring matrices. A second SPD-NGS library (Lib hP), which displayed virtually the entire human proteome tiled in contiguous 49 amino acid sequences with 25 amino acid overlaps, enabled us to identify candidate human proteome sequences. We identified up to 104 natural linear cut sites, depending on the protease, and captured most of the examples previously identified by proteomics and predicted 10- to 100-fold more. Structural bioinformatics was used to facilitate the identification of candidate natural protein substrates. SPD-NGS is rapid, reproducible, simple to perform and analyze, inexpensive, and renewable, with unprecedented depth of coverage for substrate sequences, and is an important tool for protease biologists interested in protease specificity for specific assays and inhibitors and to facilitate identification of natural protein substrates.

High-resolution epitope mapping of anti-Hu and anti-Yo autoimmunity by programmable phage display.

Paraneoplastic neurological disorders are immune-mediated diseases understood to manifest as part of a misdirected anti-tumor immune response. Paraneoplastic neurological disorder-associated autoantibodies can assist with diagnosis and enhance our understanding of tumor-associated immune processes. We designed a comprehensive library of 49-amino-acid overlapping peptides spanning the entire human proteome, including all splicing isoforms and computationally predicted coding regions. Using this library, we optimized a phage immunoprecipitation and sequencing protocol with multiple rounds of enrichment to create high-resolution epitope profiles in serum and cerebrospinal fluid (CSF) samples from patients suffering from two common paraneoplastic neurological disorders, the anti-Yo (n = 36 patients) and anti-Hu (n = 44 patients) syndromes. All (100%) anti-Yo patient samples yielded enrichment of peptides from the canonical anti-Yo (CDR2 and CDR2L) antigens, while 38% of anti-Hu patients enriched peptides deriving from the nELAVL (neuronal embryonic lethal abnormal vision like) family of proteins, the anti-Hu autoantigenic target. Among the anti-Hu patient samples that were positive for nELAVL, we noted a restricted region of immunoreactivity. To achieve single amino acid resolution, we designed a novel deep mutational scanning phage library encoding all possible single-point mutants targeting the reactive nELAVL region. This analysis revealed a distinct preference for the degenerate motif, RLDxLL, shared by ELAVL2, 3 and 4. Lastly, phage immunoprecipitation sequencing identified several known autoantigens in these same patient samples, including peptides deriving from the cancer-associated antigens ZIC and SOX families of transcription factors. Overall, this optimized phage immunoprecipitation sequencing library and protocol yielded the high-resolution epitope mapping of the autoantigens targeted in anti-Yo and anti-Hu encephalitis patients to date. The results presented here further demonstrate the utility and high-resolution capability of phage immunoprecipitation sequencing for both basic science and clinical applications and for better understanding the antigenic targets and triggers of paraneoplastic neurological disorders.

Pan-viral serology implicates enteroviruses in acute flaccid myelitis.

Since 2012, the United States of America has experienced a biennial spike in pediatric acute flaccid myelitis (AFM)1-6. Epidemiologic evidence suggests non-polio enteroviruses (EVs) are a potential etiology, yet EV RNA is rarely detected in cerebrospinal fluid (CSF)2. CSF from children with AFM (n = 42) and other pediatric neurologic disease controls (n = 58) were investigated for intrathecal antiviral antibodies, using a phage display library expressing 481,966 overlapping peptides derived from all known vertebrate and arboviruses (VirScan). Metagenomic next-generation sequencing (mNGS) of AFM CSF RNA (n = 20 cases) was also performed, both unbiased sequencing and with targeted enrichment for EVs. Using VirScan, the viral family significantly enriched by the CSF of AFM cases relative to controls was Picornaviridae, with the most enriched Picornaviridae peptides belonging to the genus Enterovirus (n = 29/42 cases versus 4/58 controls). EV VP1 ELISA confirmed this finding (n = 22/26 cases versus 7/50 controls). mNGS did not detect additional EV RNA. Despite rare detection of EV RNA, pan-viral serology frequently identified high levels of CSF EV-specific antibodies in AFM compared with controls, providing further evidence for a causal role of non-polio EVs in AFM.

Kelch-like Protein 11 Antibodies in Seminoma-Associated Paraneoplastic Encephalitis.

A 37-year-old man with a history of seminoma presented with vertigo, ataxia, and diplopia. An autoantibody specific for kelch-like protein 11 (KLHL11) was identified with the use of programmable phage display. Immunoassays were used to identify KLHL11 IgG in 12 other men with similar neurologic features and testicular disease. Immunostaining of the patient's IgG on mouse brain tissue showed sparse but distinctive points of staining in multiple brain regions, with enrichment in perivascular and perimeningeal tissues. The onset of the neurologic syndrome preceded the diagnosis of seminoma in 9 of the 13 patients. An age-adjusted estimate of the prevalence of autoimmune KLHL11 encephalitis in Olmsted County, Minnesota, was 2.79 cases per 100,000 men. (Funded by the Rochester Epidemiology Project and others.).

Chronic Meningitis Investigated via Metagenomic Next-Generation Sequencing.

Importance: Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. Objective: To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious. Design, Setting, and Participants: In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis. Main Outcomes and Measures: Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. Results: The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm. Conclusions and Relevance: Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.

Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens.

BACKGROUND: Ocular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~50 % of presumed infectious uveitis cases. The objective of this study is to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis. METHODS: This is a proof-of-concept study, in which intraocular fluid samples were obtained from five subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology. Samples were subjected to MDS, and results were compared with those from conventional diagnostic tests. Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from MDS. RESULTS: Unbiased MDS of intraocular fluid produced results concordant with known diagnoses in subjects with (n = 4) and without (n = 1) uveitis. Samples positive for Cryptococcus neoformans, Toxoplasma gondii, and herpes simplex virus 1 as tested by a Clinical Laboratory Improvement Amendments-certified laboratory were correctly identified with MDS. Rubella virus was identified in one case of chronic bilateral idiopathic uveitis. The subject's strain was most closely related to a German rubella virus strain isolated in 1992, one year before he developed a fever and rash while living in Germany. The pattern and the number of viral identified mutations present in the patient's strain were consistent with long-term viral replication in the eye. CONCLUSIONS: MDS can identify fungi, parasites, and DNA and RNA viruses in minute volumes of intraocular fluid samples. The identification of chronic intraocular rubella virus infection highlights the eye's role as a long-term pathogen reservoir, which has implications for virus eradication and emerging global epidemics.

Diagnosing Balamuthia mandrillaris Encephalitis With Metagenomic Deep Sequencing.

OBJECTIVE: Identification of a particular cause of meningoencephalitis can be challenging owing to the myriad bacteria, viruses, fungi, and parasites that can produce overlapping clinical phenotypes, frequently delaying diagnosis and therapy. Metagenomic deep sequencing (MDS) approaches to infectious disease diagnostics are known for their ability to identify unusual or novel viruses and thus are well suited for investigating possible etiologies of meningoencephalitis. METHODS: We present the case of a 74-year-old woman with endophthalmitis followed by meningoencephalitis. MDS of her cerebrospinal fluid (CSF) was performed to identify an infectious agent. RESULTS: Sequences aligning to Balamuthia mandrillaris ribosomal RNA genes were identified in the CSF by MDS. Polymerase chain reaction subsequently confirmed the presence of B. mandrillaris in CSF, brain tissue, and vitreous fluid from the patient's infected eye. B. mandrillaris serology and immunohistochemistry for free-living amoebas on the brain biopsy tissue were positive. INTERPRETATION: The diagnosis was made using MDS after the patient had been hospitalized for several weeks and subjected to costly and invasive testing. MDS is a powerful diagnostic tool with the potential for rapid and unbiased pathogen identification leading to early therapeutic targeting.

Picoinjection of microfluidic drops without metal electrodes.

Existing methods for picoinjecting reagents into microfluidic drops require metal electrodes integrated into the microfluidic chip. The integration of these electrodes adds cumbersome and error-prone steps to the device fabrication process. We have developed a technique that obviates the needs for metal electrodes during picoinjection. Instead, it uses the injection fluid itself as an electrode, since most biological reagents contain dissolved electrolytes and are conductive. By eliminating the electrodes, we reduce device fabrication time and complexity, and make the devices more robust. In addition, with our approach, the injection volume depends on the voltage applied to the picoinjection solution; this allows us to rapidly adjust the volume injected by modulating the applied voltage. We demonstrate that our technique is compatible with reagents incorporating common biological compounds, including buffers, enzymes, and nucleic acids.

Electrode-free picoinjection of microfluidic drops.

Existing methods for injecting reagents into drops utilize metal electrodes integrated into the microfluidic chip, adding cumbersome and error-prone steps to the fabrication process. Here, we introduce a method that uses the injection fluid itself as an electrode by exploiting dissolved electrolytes in the solution. This obviates the need for metal electrodes and reduces fabrication time and complexity while also affording precise control of the injected reagent volumes.