Biology subjects

Yee, C.

Publications and source records attributed to Yee, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Understanding How Actomyosin Dynamics Drive Apical Constriction by Systematically Tagging and Mapping Actin-Binding Proteins

Apical constriction shapes tissues in fundamental events including gastrulation and neural tube formation. Diverse actin regulators play key roles in shaping cells, but the spatial distribution of most actin regulators in apical constriction is unknown. Here, we describe a systematic approach revealing the endogenous localization of 49 actin regulators in C. elegans gastrulation -- nearly every actin-binding protein (ABP) expressed in the early embryo -- and we use this atlas to test mechanistic hypotheses. We found that many actin regulators localized basolaterally, dependent on the Arp2/3 complex; that linear actin assembly factors enriched apically; and that apically constricting cells had an extra requirement for membrane-cortical linkers present in all cells. These findings answer some key questions about how ABPs function in apical constriction, and they establish a rich resource for investigating actin organization throughout early C. elegans development and a systematic in vivo protein localization reference for the actin cytoskeleton community.

cell biology↗

bioRxiv2026

A Synthetic Microbial Therapy Rewires Antitumor Immunity Across Multiple Cancer Types

Microbial immunotherapies show promise against cancer, yet broad efficacy and mechanistic insight remain elusive. Here, we introduce SPIKE 1.0 (S1.0), a metabolically engineered bacterium that converts tryptophan into immunomodulatory hydroxyindoles via tryptophan monooxygenase to remodel the tumor microenvironment (TME). A single systemic dose of S1.0 elicited potent, durable antitumor responses across multiple murine models, including humanized mice, with minimal toxicity. S1.0 enhanced inflammatory signaling, activated innate and adaptive immunity, and promoted T cell persistence, memory, and resistance to exhaustion. It outperformed checkpoint inhibitors and synergized with chemotherapy. Multi-omics profiling revealed that S1.0 rewired amino acid metabolism in tumor-infiltrating immune cells and disrupted immunosuppressive networks. These results establish S1.0 as a scalable, cost-effective microbial immunotherapy with broad translational potential for solid tumors.

immunology↗

bioRxiv2025

Injury-induced tau pathology promotes aggressive behavior in Drosophila without neurodegeneration.

The microtubule-associated protein tau is implicated in neurodegenerative diseases, but its physiological roles remain poorly understood. Here, we find that pan-neuronal expression of human tau (HsTau) in Drosophila coupled with injury triggers hyper-aggression in male flies, which is absent in flies expressing non-phosphorylatable tau. These behavioral manifestations result from activation of dopaminergic circuits without neurodegeneration. Using in vitro reconstitution assays, we find that phosphorylated HsTau maintains microtubule binding but loses its ability to suppress catastrophes, thereby promoting microtubule dynamicity. In contrast, unphosphorylated HsTau and fly tau (DmTau) stabilize microtubules by reducing catastrophe frequency. Our findings challenge the canonical view of tau as a simple microtubule stabilizer and instead position it as a dynamic regulator of microtubule function and neuronal excitability. These results reveal how acute tau phosphorylation can alter neural circuit function and behavior prior to neurodegeneration, providing new insights into taus physiological and pathological roles.

neuroscience↗

bioRxiv2024

Comparison of retinol binding protein 1 with cone specific G-protein as putative effector molecules in cryptochrome signalling

Vision and magnetoreception in navigating songbirds are strongly connected as recent findings link a light dependent radical-pair mechanism in cryptochrome proteins to signalling pathways in cone photoreceptor cells. A previous yeast-two-hybrid screening approach identified six putative candidate proteins showing binding to cryptochrome type 4a. So far, only the interaction of the cone specific G-protein transducin -subunit was investigated in more detail. In the present study, we compare the binding features of the G-protein -subunit with those of another candidate from the yeast-two-hybrid screen, cellular retinol binding protein. Purified recombinant European robin retinol binding protein bound retinol with high affinity, displaying an EC50 of less than 5 nM, thereby demonstrating its functional state. We applied surface plasmon resonance and a Forster resonance transfer analysis to test for interactions between retinol binding protein and cryptochrome 4a. In the absence of retinol, we observed no robust binding events, which contrasts the strong interaction we observed between cryptochrome 4a and the G-protein -subunit. We conclude that retinol binding protein is unlikely to be involved in the primary magnetosensory signalling cascade.

biochemistry↗

bioRxiv2024

Histone deacetylase inhibition expands cellular proteostasis repertoires to enhance neuronal stress resilience

Neurons are long-lived, terminally differentiated cells with limited regenerative capacity. The maintenance of proteostasis and membrane protein trafficking is essential for neuronal function throughout development and aging. Cellular stressors, including endoplasmic reticulum (ER) protein folding stress and endosomal membrane trafficking stress, accumulate as neurons age and correlate with age-dependent neurodegeneration. However, how neurons coordinate stress responses across diverse cellular perturbations remains poorly understood. Here we demonstrate that histone deacetylases (HDACs) constrain the flexibility of neurons to engage distinct molecular pathways in response to different types of stress. Genetic or pharmacological inhibition of class I HDACs enhances neuronal resilience to both ER protein folding stress and endosomal membrane trafficking stress in C. elegans and mammalian neurons. RNA sequencing analyses in C. elegans, mouse, and human iPSC-derived neurons reveal that HDAC inhibition makes neurons more developmentally plastic and induces a permissive transcriptional state that likely represents partial cell fate reprogramming. These transcriptomic changes enable neurons to activate latent proteostasis pathways tailored to the specific nature of the stress. Given the growing excitement around partial reprogramming as a strategy to reset the epigenetic clock, our findings establish a direct link between epigenetic modulation and the neuronal stress response, pointing to new therapeutic strategies for enhancing neuronal resilience in aging and disease.

neuroscience↗

bioRxiv2024

Mass Spectrometry Imaging of the Subchondral Bone in Osteoarthritis Reveals Tissue Remodeling of Extracellular Matrix Proteins that Precede Cartilage Loss

Osteoarthritis (OA) is a degenerative condition of the skeletal extracellular matrix (ECM) marked by the loss of articular cartilage and changes to subchondral bone homeostasis. Treatments for OA beyond full joint replacement are lacking primarily due to gaps in molecular knowledge of the biological drivers of disease. Mass Spectrometry Imaging (MSI) enables molecular spatial mapping of the proteomic landscape of tissues. Histologic sections of human tibial plateaus from knees of human OA patients and cadaveric controls were treated with collagenase III to target ECM proteins prior to MS Imaging of bone and cartilage proteins using a timsTOF fleX mass spectrometer. Spatial MSI data of the knee were processed and automatically segmented identifying distinct areas of knee joint damage. ECM peptide markers were compared between i) the medial halves of OA patient joints and the medial side of non-OA (cadaveric) joints, and ii) between the same medial OA tissues and their corresponding, less OA impacted, lateral joint halves. Distinct peptide signatures distinguished OA medial tissues from the cadaveric medial and OA lateral tissues (AUROC >0.85). Overall, 31 peptide candidates from ECM proteins, including Collagen alpha-1(I), Collagen alpha-1(III), and surprisingly, Collagen alpha-1(VI) and Collagen alpha-3(VI), exhibited significantly elevated abundance in diseased tissues. Highly specific hydroxyproline-containing collagen peptides, mainly from collagen type I, dominated OA subchondral bone directly under regions of lost cartilage. The identification of specific protein markers for subchondral bone remodeling in OA advances our molecular understanding of disease progression in OA and provides potential new biomarkers for OA detection and disease grading.

cell biology↗

bioRxiv2023

pan-MHC and cross-Species Prediction of T Cell Receptor-Antigen Binding

Profiling the binding of T cell receptors (TCRs) of T cells to antigenic peptides presented by MHC proteins is one of the most important unsolved problems in modern immunology. Experimental methods to probe TCR-antigen interactions are slow, labor-intensive, costly, and yield moderate throughput. To address this problem, we developed pMTnet-omni, an Artificial Intelligence (AI) system based on hybrid protein sequence and structure information, to predict the pairing of TCRs of {beta} T cells with peptide-MHC complexes (pMHCs). pMTnet-omni is capable of handling peptides presented by both class I and II pMHCs, and capable of handling both human and mouse TCR-pMHC pairs, through information sharing enabled this hybrid design. pMTnet-omni achieves a high overall Area Under the Curve of Receiver Operator Characteristics (AUROC) of 0.888, which surpasses competing tools by a large margin. We showed that pMTnet-omni can distinguish binding affinity of TCRs with similar sequences. Across a range of datasets from various biological contexts, pMTnet-omni characterized the longitudinal evolution and spatial heterogeneity of TCR-pMHC interactions and their functional impact. We successfully developed a biomarker based on pMTnet-omni for predicting immune-related adverse events of immune checkpoint inhibitor (ICI) treatment in a cohort of 57 ICI-treated patients. pMTnet-omni represents a major advance towards developing a clinically usable AI system for TCR-pMHC pairing prediction that can aid the design and implementation of TCR-based immunotherapeutics.

immunology↗

bioRxiv2023

A NanoDam toolkit for tissue-specific transcription factor profiling in C. elegans

During development of multicellular organisms, cells must execute precise molecular decisions to achieve cell fate specification and differentiation. These decisions are orchestrated by networks of transcription factors (TFs) which act to regulate gene expression of specific cohorts of genes to ultimately confer identity. Depending on the cellular context, TF expression can vary dramatically both spatially and temporally. These differences in expression patterns can result in tissue-specific differences in TF binding to downstream targets. To identify targets on a tissue-specific basis, Targeted DamID (TaDa) has been recently introduced to generate TF binding profiles in various models including C. elegans. However, TaDa suffers from portability such that a new promoter-TF fusion transgene must be constructed for every new experimental condition of interest. Here, we adapt NanoDam for usage in C. elegans, which relies on endogenous TF-GFP knock-ins, a plethora of which have already been generated by the community. We report that NanoDam single copy transgenes consisting of lowly expressed, tissue-specific GFP nanobody-Dam fusions, when combined with endogenous GFP-tagged alleles of TFs, results in robust, tissue-specific profiling. Using an endogenous GFP-tagged allele of EGL-43/EVI1, we performed NanoDam profiling of two disparate tissue types, the anchor cell (AC) and dopaminergic neurons, and identify targets unique to each and shared by both cell types. We also identify two GATA TFs, ELT-6 and EGL-18, as novel regulators of AC invasion. Together, we demonstrate that NanoDam is capable of profiling endogenous GFP-tagged TFs to identify novel downstream targets in specific cell types of C. elegans.

genetics↗

bioRxiv2023

Model Parameter identification using 2D vs 3D experimental data: a comparative analysis

Computational models are becoming an increasingly valuable tool in biomedical research. They enable the quantification of variables difficult to measure experimentally, an increase in the spatio-temporal resolution of the experiments and the testing of hypotheses. Parameter estimation from in-vitro data, remains a challenge, due to the limited availability of experimental datasets acquired in directly comparable conditions. While the use of computational models to supplement laboratory results contributes to this issue, a more extensive analysis of the effect of incomplete or inaccurate data on the parameter optimization process and its results is warranted. To this end, we compared the results obtained from the same in-silico model of ovarian cancer cell growth and metastasis, calibrated with datasets acquired from two different experimental settings: a traditional 2D monolayer, and 3D cell culture models. The differential behaviour of these models will inform the role and importance of experimental data in the calibration of computational models calibration. This work will also provide a set of general guidelines for the comparative testing and selection of experimental models and protocols to be used for parameter optimization in computational models Author summaryParameter identification is a key step in the development of a computational model, that is used to establish a connection between the simulated and experimental results and verify the accuracy of the in-silico framework. The selection of the in-vitro data to be used in this phase is fundamental, but little attention has been paid to the role of the experimental model in this process. To bridge this gap we present a comparative analysis of the same computational model calibrated using experimental data acquired from cells cultured (i) in 2D monolayers, (ii) in 3D culture models and (iii) a combination of the two. Data acquired in different experimental settings induce changes in the optimal parameter sets and the corresponding computational models behaviour. This translates in a varying degree of accuracy during the validation procedure, when the simulated data are compared to experimental measurements not used during the calibration step. Overall, our work provides a workflow and a set of guidelines to select the most appropriate experimental setting for the calibration and validation of computational models.

bioengineering↗

bioRxiv2022

An expandable FLP-ON::TIR1 system for precise spatiotemporal protein degradation in C. elegans

The auxin-inducible degradation system has been widely adopted in the C. elegans research community for its ability to empirically control the spatiotemporal expression of target proteins. This system can efficiently degrade auxin-inducible degron (AID)-tagged proteins via the expression of a ligand-activatable AtTIR1 protein derived from A. thaliana that adapts target proteins to the endogenous C. elegans proteosome. While broad expression of AtTIR1 using strong, ubiquitous promoters can lead to rapid degradation of AID-tagged proteins, cell type-specific expression of AtTIR1 using spatially restricted promoters often results in less efficient target protein degradation. To circumvent this limitation, we have developed a FLP/FRT3-based system that functions to reanimate a dormant, high-powered promoter that can drive sufficient AtTIR1expression in a cell type-specific manner. We benchmark the utility of this system by generating a number of tissue specific FLP-ON::TIR1 drivers to reveal genetically separable cell type-specific phenotypes for several target proteins. We also demonstrate that the FLP-ON::TIR1 system is compatible with enhanced degron epitopes. Finally, we provide an expandable toolkit utilizing the basic FLP-ON::TIR1 system that can be adapted to drive optimized AtTIR1expression in any tissue or cell type of interest.

developmental biology↗

bioRxiv2022

A reevaluation of the relationship between EGL-43 (EVI1/MECOM) and LIN-12 (Notch) during C. elegans anchor cell invasion

Development of the C. elegans reproductive tract is orchestrated by the anchor cell (AC). Among other things, this occurs through a cell invasion event that connects the uterine and vulval tissue. Several key transcription factors regulate AC invasion, such as EGL-43, HLH-2, and NHR-67. Specifically, these transcription factors function together to maintain the post-mitotic state of the AC, a requirement for AC invasion. EGL-43 is the C. elegans homolog of the human EVI1/MECOM proto-oncogene, and recently, a mechanistic connection has been made between its loss and AC cell-cycle entry. The current model states that EGL-43 represses LIN-12 (Notch) expression to prevent AC proliferation, suggesting that Notch signaling is mitogenic in the absence of EGL-43. To reevaluate the relationship between EGL-43 and LIN-12, we designed and implemented a heterologous co-expression system called AIDHB that combines the auxin-inducible degron (AID) system of plants with a live cell-cycle sensor based on human DNA helicase B (DHB). After validating the AIDHB approach using AID-tagged GFP, we sought to test this approach using AID-tagged alleles of egl-43 and lin-12. Auxin-inducible degradation of either EGL-43 or LIN-12 resulted in the expected AC phenotypes. Lastly, we seized the opportunity to pair AIDHB with RNAi to co-deplete LIN-12 and EGL-43, respectively. This combined approach revealed that LIN-12 is not required for AC proliferation following loss of EGL-43, which contrasts with a double RNAi experiment directed against these same targets. The addition of AIDHB to the C. elegans transgenic toolkit should facilitate functional in vivo imaging of cell-cycle associated phenomena.

developmental biology↗

bioRxiv2022

Transcriptional regulation and repressive condensates modulate a proliferative-invasive cellular switch in vivo

A growing body of evidence suggests that cell division and basement membrane invasion are mutually exclusive cellular behaviors. How cells switch between proliferative and invasive states is not well understood. Here, we investigated this dichotomy in vivo by examining two cell types in the developing Caenorhabditis elegans somatic gonad that derive from equipotent progenitors, but exhibit distinct cell behaviors: the post-mitotic, invasive anchor cell and the neighboring proliferative, non-invasive ventral uterine (VU) cells. We show that the fates of these cells post-specification are more plastic than previously appreciated and that levels of NHR-67 are important for discriminating between invasive and proliferative behavior. Transcription of nhr-67 is downregulated following post-translational degradation of its direct upstream regulator, HLH-2 (E/Daughterless) in VU cells. In the nuclei of VU cells, residual NHR-67 protein is compartmentalized into discrete punctae that are dynamic over the cell cycle and exhibit liquid-like properties. By screening for proteins that colocalize with NHR-67 punctae, we identified new regulators of uterine cell fate maintenance: homologs of the transcriptional co-repressor Groucho (UNC-37 and LSY-22), as well as the TCF/LEF homolog POP-1. We propose a model in which association of NHR-67 with the Groucho/TCF complex suppresses the default invasive state in non-invasive cells, which complements transcriptional regulation to add robustness to the proliferative-invasive cellular switch in vivo.

developmental biology↗

bioRxiv2021

Immunogenic SARS-CoV2 Epitopes Defined by Mass Spectrometry

SARS-CoV-2 infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID19, the disease caused by SARS-CoV-2, T cell responses are important in mediating recovery and immune-protection. The identification of immunogenic epitopes that can elicit a meaningful T cell response can be elusive. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes; however, our previous studies find that immunodominant SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing SARS-CoV-2. We postulated that immunogenic epitopes for SARS-CoV-2 are best defined by directly analyzing peptides eluted from the peptide-MHC complex and then validating immunogenicity empirically by determining if such peptides can elicit T cells recognizing SARS-CoV-2 antigen-expressing cells. Using a tandem mass spectrometry approach, we identified epitopes of SARS-CoV-2 derived not only from structural but also non-structural genes in regions highly conserved among SARS-CoV-2 strains including recently recognized variants. We report here, for the first time, several novel SARS-CoV-2 epitopes from membrane glycol-protein (MGP) and non-structure protein-13 (NSP13) defined by mass-spectrometric analysis of MHC-eluted peptides, provide empiric evidence for their immunogenicity to induce T cell response. Significance StatementCurrent state of the art uses putative epitope peptides based on in silico prediction algorithms to evaluate the T cell response among COVID-19 patients. However, none of these peptides have been tested for immunogenicity, i.e. the ability to elicit a T cell response capable of recognizing endogenously presented peptide. In this study, we used MHC immune-precipitation, acid elution and tandem mass spectrometry to define the SARS-CoV-2 immunopeptidome for membrane glycol-protein and the non-structural protein. Furthermore, taking advantage of a highly robust endogenous T cell (ETC) workflow, we verify the immunogenicity of these MS-defined peptides by in vitro generation of MGP and NSP13 peptide-specific T cells and confirm T cell recognition of MGP or NSP13 endogenously expressing cell lines.

immunology↗

bioRxiv2021

In Silico Defined SARS-CoV2 Epitopes May Not Predict Immunogenicity to COVID19

SARS-CoV-2 infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID19, the disease caused by SARS-CoV-2, it has become increasingly apparent that T cell responses are equally, if not more important than humoral responses in mediating recovery and immune-protection. One of the major challenges in developing T cell-based therapies for infectious and malignant diseases has been the identification of immunogenic epitopes that can elicit a meaningful T cell response. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes deduced from binding affinities and consensus data. Our studies find that, in contrast to current dogma, immunodominant SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing naturally presented SARS-CoV-2 epitopes.

immunology↗

bioRxiv2020

Single-dose intranasal vaccination elicits systemic and mucosal immunity against SARS-CoV-2

A safe and durable vaccine is urgently needed to tackle the COVID19 pandemic that has infected >15 million people and caused >620,000 deaths worldwide. As with other respiratory pathogens, the nasal compartment is the first barrier that needs to be breached by the SARS-CoV-2 virus before dissemination to the lung. Despite progress at remarkable speed, current intramuscular vaccines are designed to elicit systemic immunity without conferring mucosal immunity. We report the development of an intranasal subunit vaccine that contains the trimeric or monomeric spike protein and liposomal STING agonist as adjuvant. This vaccine induces systemic neutralizing antibodies, mucosal IgA responses in the lung and nasal compartments, and T-cell responses in the lung of mice. Single-cell RNA-sequencing confirmed the concomitant activation of T and B cell responses in a germinal center-like manner within the nasal-associated lymphoid tissues (NALT), confirming its role as an inductive site that can lead to long-lasting immunity. The ability to elicit immunity in the respiratory tract has can prevent the initial establishment of infection in individuals and prevent disease transmission across humans.

immunology↗

bioRxiv2020

Coffee consumption and risk of breast cancer: a Mendelian Randomization study

BackgroundObservational studies have reported either null or weak protective associations for coffee consumption and risk of breast cancer. MethodsWe conducted a two-sample Mendelian randomization randomization (MR) analysis to evaluate the relationship between coffee consumption and breast cancer risk using 33 single-nucleotide polymorphisms (SNPs) associated with coffee consumption from a genome-wide association (GWA) study on 212,119 female UK Biobank participants of White British ancestry. Risk estimates for breast cancer were retrieved from publicly available GWA summary statistics from the Breast Cancer Association Consortium (BCAC) on 122,977 cases (of which 69,501 were estrogen receptor (ER)-positive, 21,468 ER-negative) and 105,974 controls of European ancestry. Random-effects inverse variance weighted (IVW) MR analyses were performed along with several sensitivity analyses to assess the impact of potential MR assumption violations. ResultsOne cup per day increase in genetically predicted coffee consumption in women was not associated with risk of total (IVW random-effects; odds ratio (OR): 0.91, 95% confidence intervals (CI): 0.80-1.02, P: 0.12, P for instrument heterogeneity: 7.17e-13), ER-positive (OR=0.90, 95% CI: 0.79-1.02, P: 0.09) and ER-negative breast cancer (OR: 0.88, 95% CI: 0.75-1.03, P: 0.12). Null associations were also found in the sensitivity analyses using MR-Egger (total breast cancer; OR: 1.00, 95% CI: 0.80-1.25), weighted median (OR: 0.97, 95% CI: 0.89-1.05) and weighted mode (OR: 1.00, CI: 0.93-1.07). ConclusionsThe results of this large MR study do not support an association of genetically predicted coffee consumption on breast cancer risk, but we cannot rule out existence of a weak inverse association.

cancer biology↗

bioRxiv2020

Immune landscape of a genetically-engineered murine model of glioma relative to human glioma by single-cell sequencing

BackgroundThis study focuses on the evaluation of intratumoral immune infiltrates of the Qk/trp53/Pten (QPP) triple-knockout mouse model of glioblastoma with the purpose of establishing its relevance compared to the human disease. This included an analysis at the single cell level, of immune cells composition in both spontaneous and implanted mouse tumors and of samples obtained from human tumor resections. MethodsWe analyzed a cohort of fifteen spontaneous QPP mice, nine implanted QPP mice and 10 glioma patients by standard immune profiling methods such as IHC. Of those, we analyzed three spontaneous QPP mice, three implanted QPP mice, and 10 glioma patients by single cell RNA sequencing. ResultsIn the QPP samples we identified a predominantly myeloid cell population of monocytes, macrophages, and microglia, with minor populations of T, B, and NK cells. When comparing spontaneous and implanted mouse samples, we found that there were more neutrophil, T and NKT cells in the implanted model. In human samples, most of the lymphoid and myeloid compartments were immunosuppressive. While the complexity of the myeloid cell populations is preserved between the QPP model and the human disease, we observed significantly more immune-stimulatory populations in the implanted mouse model. ConclusionsWe found that, despite differences at the subpopulation level, the immunosuppressive nature of the immune system in glioma, is recapitulated in our mouse model. Although we observed differences in the proportions of immune infiltrates derived from the spontaneous and implanted mouse models and in LGG compared to GBM, the major constituents are present in all cases and these differences may be caused by various etiological or pathogenic influences on tumor-immune interactions. Key PointsO_LINew GBM mouse model for immunotherapy C_LIO_LISingle cell profiling of the immune systems in human and mouse GBM C_LI

cancer biology↗

bioRxiv2020

Proteomic changes in bacteria caused by exposure to environmental conditions can be detected by Matrix-Assisted Laser Desorption/Ionization - Time of Flight (MALDI-ToF) Mass Spectrometry

In the past decade, matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) mass spectrometry (MS) has become a timely and cost-effective alternative to bacterial identification. The MALDI-ToF MS technique analyzes the total protein of culturable microorganisms at the species level and produces a mass spectra based on peptides which is compared to a database of identified profiles. Consequently, unique signatures of each microorganism are produced allowing identification at the species and, more importantly, strain level. Our present study proposes that the MALDI-ToF MS can be further used to screen functional and metabolic differences. While other studies applied the MALDI-ToF technique to identify subgroups within species, we investigated how various environmental factors could alter the unique bacterial signatures. We found that genetic and phenotypic differences between microorganisms belonging to the same species can be reflected in peptide-mass fingerprints generated by MALDI-ToF MS. These results suggest that MALDI-ToF MS can screen intra-species phenotypic differences of several microorganisms.

microbiology↗