Cognitive impairment (CI) is very common in patients with Parkinson’s Disease (PD) and progressively develops on a spectrum from mild cognitive impairment (PD-MCI) to full dementia (PDD). Identification of PD patients at risk of developing cognitive decline, therefore, is unmet need in the clinic to manage the disease. Previous studies reported that oral microbiota of PD patients was altered even at early stages and poor oral hygiene is associated with dementia. However, data from single modalities are often unable to explain complex chronic diseases in the brain and cannot reliably predict the risk of disease progression. Here, we performed integrative metaproteogenomic characterization of salivary microbiota and tested the hypothesis that biological molecules of saliva and saliva microbiota dynamically shift in association with the progression of cognitive decline and harbor discriminatory key signatures across the spectrum of CI in PD. We recruited a cohort of 115 participants in a multi-center study and employed multi-omics factor analysis (MOFA) to integrate amplicon sequencing and metaproteomic analysis to identify signature taxa and proteins in saliva. Our baseline analyses revealed contrasting interplay between the genus Neisseria and Lactobacillus and Ligilactobacillus genera across the spectrum of CI. The group specific signature profiles enabled us to identify bacterial genera and protein groups associated with CI stages in PD. Our study describes compositional dynamics of saliva across the spectrum of CI in PD and paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD. Due to the impact of the ageing population, a considerable increase in PD cases is expected in thefuture decades2. PD physiopathology is attributed to the alpha-synuclein (α-syn) aggregates accumulating in the neurons, which causes significant disruption of both motor and non-motor functions in the course of the disease3. One of its most common non-motor symptoms is cognitive impairment (CI) that progressively develops on a spectrum from mild cognitive impairment (MCI) to full-scale dementia (PDD)4. Despite variability among patients, there is a high risk of dementia in PD, with nearly half of patients reaching the dementia stage within 10 years after diagnosis and virtually all patients develop full dementia within 20 years after diagnosis5. These patients cannot live independent lives and require care and support from their families and nursing homes, leading to economic burden. Thus, the current unmet need in the clinic is whether the PD patients at risk of developing cognitive decline can be predicted in order to implement disease changing interventions.Parkinson’s disease (PD) is a complex neurodegenerative disorder estimated to affect over 6 million people worldwide6. The oral health of PD patients such as saliva secretion, the composition of saliva, and dysbiosis significantly aggravate in the course of the disease7. Indeed, α-Syn can be detected in different biological fluids, including cerebrospinal fluid (CSF) and saliva10. The alpha-synuclein pathology in the oral cavity of PD patients often leads to poor secretion of saliva and dysphagia12. Remarkably, a 6-year follow-up study of dysphagia in PD patients reported a significant association between CI and dysphagia13. Another common oral motor disorder of PD is drooling which has also been associated with CI in PD14. Together, these findings suggest a link between oral problems and CI in PD. Furthermore, recent studies reporting oral microbiota dysbiosis of PD patients linked dysphagia, drooling, and salivary pH with oral microbiota16. Therefore, we hypothesized that biological molecules of saliva and saliva microbiota dynamically shift in association with CI progression in PD and harbors discriminatory key signature changes for predicting CI stages in PD.Saliva is a complex biofluid and considered to be a rich source of potential biomarkers for chronic diseases as saliva components typically include host cells, microbiota and biological moleculesmetaproteomics data generated from saliva samples. We recruited 115 subjects to identify changes in saliva composition that can be used to differentiate PD patients at different CI stages. We determined that salivary microbiota differentiates CI stages and detected bacterial taxa associated with CI. We also identified functional level changes associated with CI in PD, and highlighted a short list of candidate signatures differentiating CI stages in PD.To test the hypothesis, we employed metaproteogenomics approach by integrating 16 S rRNA gene amplicon sequencing and A total of 115 individuals  and 27 HC were included in this study. Both 16 S rRNA gene amplicon sequencing based microbiome analysis and metaproteomics profiling were performed for all salivary samples collected from the participants . To strengthen the conclusion, we also we used the Bray-Curtis and Jaccard distance for 16 S rRNA gene amplicon sequencing results to test differences between study groups, which also showed a significant separation between the three groups   between study groups Fig. . On the 17, we used three different methods and sought consensus between at least two of these methos in detecting differential abundance. ANOVA-based differential abundance analysis showed a significant decrease in the abundance of Neisseria genus and unclassified Neisseriacceae with the progression of CI  and a significant negative correlation between Neisseria and CDR score   ; although when adjusted for all potential confounders, the difference was attenuated   were from salivary microorganisms while 250 46.5%) protein groups were from human proteome origin. Human protein groups constituted 67.9% of the total protein intensities measured in the salivary samples while microbial protein groups constituted 32.1% of total protein intensities Fig.  which sh6.5% prot82) Fig. .Fig. 4MeIn order to assess changes in the functional profile of samples, we annotated protein groups using Prophane and applied differential abundance tests both at OG and functional category levels. We have obtained 371 OGs from 24 functional categories and 25 differentially abundant OGs between study groups. At the OG level analysis, functions related to the replication, recombination, and repair (5 OGs in category L), cytoskeleton (4 OGs in category Z), energy production and conversion (3 OGs in category C), translation, ribosomal structure, and biogenesis (2 OGs in category J) were among the most significantly different categories between study groups. 20 of differentially abundant OGs were significantly increased with the progression of CI while 5 OGs showed an increase from HC to MCI and a decrease from MCI to PDD Fig. . The difAt the functional category level, energy production and conversion and inorganic ion transport and metabolism categories were significantly increased with the progression of CI while defense mechanisms and secondary metabolites biosynthesis, transport and catabolism displayed a decreased abundance Fig. .R2 = 0.064, p = 0.003) and identified the contributing features of this factor. Factor 2 values positively correlated with the progression of CI , intracellular trafficking, secretion, and vesicular transport (category U), replication, recombination and repair (category L) and unknown function (category S) and a decreased abundance of proteins associated with carbohydrate transport and metabolism (category G) and defense mechanisms (category V).We applied MOFA to integrate amplicon sequencing and metaproteome results. The fitted model explained 30.1% and 34.4% of the variance in 16 S rRNA sequencing and metaproteomics datasets, respectively Fig.  with lat CI Fig. . Amplicon = 27; PD-MCI, n = 45; PDD, n = 43; PDNC, n = 8) and 40 samples  from a published study)15. Alpha diversity comparisons showed no significant difference between sample groups   ) and bactericidal permeability-increasing protein (BPI) identified in our previous analysis without PDNC group.Furthermore, we repeated MOFA analysis adding 8 PDNC samples as the fourth sample group to our cohort. We examined potential correlations between factors and covariates and determined the association of Factor 2 primarily with CI in PD and Disease Duration  as compared with HC using both 16 S rRNA gene amplicon sequencing and metaproteomics profiling. We identified the discriminatory key signatures in saliva composition related to CI stages of PD by applying an integrative metaproteogenomics approach. Employing an integrative analysis of saliva metagenomics and metaproteomics, we demonstrated that a shift in salivary microbiome and protein translation machinery and defense mechanism related changes in human proteome is associated with the CI progression in PD.Streptococcus, Prevotella, Veillonella, Fusobacterium and Neisseria as the most abundant bacterial genera in the study cohort which is in agreement with a previous study comparing salivary microbiota of healthy controls and PD patients15. The amplicon sequencing detected much more bacterial genera, families, and phyla than metaproteomics profiling. This is not surprising because only a subset of bacterial genera (as described in the Methods) were used to generate a custom-based reference protein database to identify proteins.Both metaproteome and microbiota profiles indicated Neisseria genus with the progression of CI, which aligned well with the previously published reports20. Here, we further showed the continuous decrease of Neisseria with the progression of CI in PD.Although alpha diversity in amplicon-based microbiota showed no significant differences between study groups beta diversity comparisons of saliva samples significantly differentiated CI stages, suggesting salivary bacterial community restructures by the progression of CI. Results of four differential abundance methods showed in consensus a significant decrease of 18. Differential abundance analyses of metaproteome profiles determined marked functional alterations associated with CI. Particularly, the functions related to cytoskeleton and translation, ribosomal structure and biogenesis, defense mechanisms and energy production and conversion were among the most significantly altered functions between study groups.The metaproteome profile of saliva samples was composed of a balanced number of human and bacterial protein groups. On the other hand, human proteins constituted much higher percentage of total protein intensities measured in the saliva samples, as observed in previous studiesNeisseria deserves special attention among others as it is implicated in prevention of oral diseases due to its beneficial abilities such as metabolizing low-pH products into weak acids. On the other hand, consistently reported high abundance of Lactobacillaceae members in the oral cavity of PD patients may have negative effects due to their ability to reduce secretion of neuroprotective hormones such as ghrelin21. The decrease in Neisseria accompanied with the increased abundance of Lactobacillaceae family has been also reported in a recent study on PD16. Our results suggest a continuity for this compositional shift across CI spectrum in PD. Moreover, we have detected a decrease in PPDK enzyme, as another signature. PPDK is known as one of key enzymes in gluconeogenesis22 and related to lactic acid production23. Furthermore, we detected BPI as another signature protein group, which is involved in the defense of host against bacterial pathogens and considered as a microbial translocation markers24. Elevated serum endotoxin levels have been previously reported in PD patients, which indicate greater bacterial translocation, particularly for the subgroup with high risk for early dementia25. Thus, our observation of decreased BPI abundance in saliva suggests a potential LPS-BPI imbalance in PD patients which worsens with the CI progression.The taxa In conclusion, our study presents a comprehensive overview of significant key changes in saliva composition that parallel the progression of CI in PD and suggests potential non-invasive biomarker candidates for predicting CI in PD by integrating amplicon sequencing and metaproteomics. This approach paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD.The conclusions drawn from the data we presented in this manuscript should be interpreted under the following considerations.In spite of the valuable insights gained from our microbiome study, it is essential to acknowledge the limitations that may impact the interpretation and generalizability of our findings. The absence of adequate controls for confounding variables, such as dietary habits  and medication usage may introduce biases and hinder our ability to establish direct causal relationships between the microbiome and cognitive impairment in PD. Another limitation is the poor representation of PD patients without cognitive impairment (PDNC) in our cohort as a comparison group. Even though we attempted to rectify this limitation in our study design by adding published data generated from PDNC group we were unable to pinpoint a dataset including both metaproteomics and amplicon sequencing from the same saliva samples obtained from PDNC group. Thus, even though the microbial taxa found to be associated with CI in our study is robust we have less confidence in the saliva proteins linked with the confidence impairment due to the poor representation of PDNC group in our cohort. Regardless, these findings should be validated in a prospective longitudinal study in the future. Despite these limitations, however, our study contributes valuable preliminary insights into associations of putative saliva biomarkers with CI in PD. Future research endeavors should aim to address these confounding factors rigorously.n = 27; PD-MCI, n = 45; PDD, n = 43) within the age range of 50-75 were recruited at two tertiary training hospitals including the Medipol Training and Research Hospital in the neurology clinic and Bakirkoy Research and Training Hospital for Psychiatric and Neurological Diseases. The subjects in the HC group were recruited largely from the family members of the patients and also some family members of the hospital employees and of the students, otherwise from the individuals who responded to the advertisement of the clinical study. All control group participants were required to take formal neuropsychological testing and assessed by the clinician on their cognitive capacity, and by the exclusion criteria of the study. Subjects with previous head trauma, stroke, or exposure to toxic substances, substance abuse, history of antibiotic or probiotic use within last 1-month, chronic severe diseases , autoimmune diseases, smokers, pregnancy, and those with symptoms suggestive of Parkinson’s plus syndromes were excluded from the study. Clinical and demographic information, including age, sex, years of education were collected at clinic visits. The patients were examined by experienced neurologists and the diagnosis of PD was made within the framework of the “United Kingdom Parkinson’s Disease Society Brain Bank” criteria. Hoehn-Yahr Stages Parkinson’s Staging Scale was used to determine the stage of the disease and The Movement Disorder Society’s diagnostic criteria for Parkinson’s Disease Dementia criteria were used for dementia evaluation according to Emre et al.26 The diagnosis of MCI was made within the framework of the criteria defined by Litvan et al.27 according to level II criteria .The study was approved by the ethics committee of the Istanbul Medipol University with authorization number 10840098-604.01.01-E.3958, and informed consent was obtained from all participants. If the patient has progressed into dementia stage and was not able to make independent assessment of the consent form, consent of the patient’s immediate family member  was obtained. A total of 115 subjects . After bead-beating step, the manufacturer’s protocol was followed without any modification. The V3-V4 regions of 16 S rRNA gene were amplified using the universal bacterial primers (F-5′-CCTACGGGNGGCWGCAG-3′ and R-5′-GACTACHVGGGTATCTAATCC-3′). Next, amplicon libraries were prepared by following Illumina’s 16 S rRNA metagenomic sequencing library preparation protocol and sequenced using a MiSeq platform and 2 × 250 paired end kit. Amplicon sequencing libraries prepared from a total of 115 gDNA samples were sequenced along with DNA extraction negative control and a no-template PCR control per run.Unstimulated saliva samples were divided into two equal aliquots of 500 ml and used for DNA and protein extractions separately. Microbial DNA extraction from saliva samples was performed using DNeasy PowerSoil  with modifications as described before29.For protein extraction, 250 ml saliva sample was centrifuged at 10,000 x g for 5 min. Discarding the supernatant, the pellet was resuspended in 250 μl bead beating buffer and transferred to the BeadBug™ prefilled tubes, 2.0 ml containing 1.0 mm Zirconium beads. Samples were homogenized by bead-beating using Next Advance Bullet Blender . After bead-beating step, samples were incubated at 100 °C for 10 min under constant shaking (600 rpm), followed by 4 °C incubation for an hour and centrifugation at 16,000 × g for 10 min. The supernatants were finally transferred to a clean 1.5 ml microcentrifuge tube. The total protein concentrations were measured using the Qubit protein assay kit. 50 µg protein (eluted in 30 µl) was used in the downstream analyses for each sample. Tryptic peptides were generated using the Filter Aided Sample Preparation Protocol (FASP) kit  according to the manufacturer’s protocol. The peptides were dissolved in 0.1 percent formic acid and diluted to 100 ng/μl before injecting to the liquid chromatography tandem-mass spectrometry ). The LC-MS/MS analysis was performed according to a previously published protocolhttp://nephele.niaid.nih.gov)30 using default parameters  and SILVA v.138.1 database31. The contaminant sequences were identified and removed using the decontam package32 based on negative control samples. Only ASVs present in at least 2 samples were included in the downstream analyses. Samples were rarefied to minimum sampling depth  before performing alpha diversity analyses and CLR transformed before beta diversity analyses. Diversity analyses were performed using QIIME233 and phyloseq34. MaAsLin235, LEfSe36, ANCOM-BC37 and ANOVA tests were used to determine differential abundances between groups, controlling covariates when possible. The R package ggplot238 was used for visualization of the results.Raw 16 S rRNA gene amplicon sequencing data were analyzed using the Nephele platform  software was used to identify and quantify the protein groups. Protein groups identified by at least 2 unique peptide sequences, taxonomically assigned to Eukaryota or Bacteria kingdoms and present in all samples were used for downstream analyses. Also, to reduce batch effects on metaproteomics results, we used MMUPHin41 to adjust protein abundances before further processing. Diversity analyses were performed using phyloseq. We employed Prophane42 tool with default parameters to annotate taxonomy and functions of the detected proteins. All identified protein groups from each sample were classified into main metabolic pathways using the orthologous groups (OG) classification against the EggNog database43. ANOVA was used to examine potential associations at both the protein OGs and functional categories levels with CI stages.For metaproteomics data analysis, firstly, a custom protein database based on 16 S rRNA amplicon sequencing results was built. Briefly, we determined the top 20 most abundant bacterial genera across study groups. We obtained all species-level genome bins that belonged to these genera from a recently published comprehensive study on human oral microbiome44 was employed to integrate 16 S rRNA amplicon sequencing and metaproteomics datasets as data modalities with matching samples. ASV table was collapsed to the genus level and both datasets were centered log ratio (CLR) transformed to reduce compositionality bias before generating the MOFA model. Data and training options were set to default with 10,000 iterations in ‘slow’ convergence mode to generate 15 factors. Downstream analyses after generation of MOFA model were performed using MOFA+ tool45.Multi-Omics Factor Analysis (MOFA)15 that employed 16 S rRNA gene amplicon sequencing. This study compared 20 PDNC to 20 HC, targeting the V3-V4 region of the 16 S rRNA gene and using the same primer set we used in this study. We followed the same analysis steps as described earlier to reinforce our findings and validate the association of specific bacterial genera with PD-MCI and PDD groups. Secondly, we gathered an additional 8 PDNC samples and analyzed them using metaproteomics and amplicon sequencing techniques.We used two approaches to verify the reliability of our findings regarding the correlation between our selected features and CI in PD. Firstly, we incorporated data from a previously published study conducted by Fleury et al.t-test was used for continuous variables, namely age and education, while Fisher’s exact test was used for categorical variables. All p-values, where appropriate, were adjusted for multiple testing using the Benjamini-Hochberg method. Adjusted p-values are denoted by “adj.p” and raw p-values are denoted by “p” throughout the manuscript. Results of all statistical tests are provided in the Supplementary File Statistical analyses were conducted in R 3.6.1. A Kruskal-Wallis test was used for alpha diversity comparisons. Adonis2, an implementation of permutational multivariate analysis of variance (PERMANOVA) from the vegan package with 999 permutations, was used for beta diversity comparisons, with adjustment for potential confounding factors Age, Sex, Education, Disease Duration and HYE. Linear regression analysis was performed to test association of latent factors generated by MOFA, with adjustment for potential confounding factors. A Further information on research design is available in the Supplementary file 1Reporting Summary


Exertional heat illness (EHI) is an occupational health hazard for athletes and military personnel–characterised by the inability to thermoregulate during exercise. The ability to thermoregulate can be studied using a standardised heat tolerance test (HTT) developed by The Institute of Naval Medicine. In this study, we investigated whole blood gene expression  in male subjects with either a history of EHI or known susceptibility to malignant hyperthermia (MHS): a pharmacogenetic condition with similar clinical phenotype. Compared to healthy controls at baseline, 291 genes were differentially expressed in the EHI cohort, with functional enrichment in inflammatory response genes (up to a four-fold increase). In contrast, the MHS cohort featured 1019 differentially expressed genes with significant down-regulation of genes associated with oxidative phosphorylation (OXPHOS). A number of differentially expressed genes in the inflammation and OXPHOS pathways overlapped between the EHI and MHS subjects, indicating a common underlying pathophysiology. Transcriptome profiles between subjects who passed and failed the HTT  were not discernable at baseline, and HTT was shown to elevate inflammatory response gene expression across all clinical phenotypes. Exertional heat illness (EHI) causes injury and death through the effects of salt and water depletion, direct thermal tissue damage, or a combination of these. It results from a failure to dissipate the heat generated by intense and sustained metabolic activity of voluntary muscles . It occu2 max scores and lower maximal workloads than healthy controls during maximal exercise on a cycloergometer, more than 5 months after they presented with EHI. They also demonstrated a limited thermoregulatory capacity, with higher body temperature post-exercise than the healthy controls. Plasma-free fatty acids, glycerol and blood lactate concentrations were significantly higher in the EHI patients during and after exercise, suggesting increased lipolysis and impairment of the oxidative phosphorylation (OXPHOS) pathway.Vanuxem et al. measured exercise capacity and muscle energy metabolism in military personnel recovering from EHI episodes, featuring hyperthermia (≥40 °C), neurological impairment and rhabdomyolysis . An EHI Based on in vitro skeletal muscle pharmacological contracture tests (IVCT) that are used to diagnose susceptibility to malignant hyperthermia  we idenRYR1  in the heritability of EHI but suggested genetic heterogeneity and a multigenic model. We found non-polymorphic potentially pathogenic variants in genes encoding proteins involved in skeletal muscle calcium homeostasis, oxidative metabolism and membrane excitability [Genetic analyses of our EHI cohort have confirmed the role of tability . While iOne approach to elucidating molecular and cellular mechanisms of EHI and underlying genetic defects is to identify differential gene expression affecting individual genes and biological pathways or processes between survivors of EHI and controls. Here we report whole blood gene expression before  and after the subjects undertook a standardised HTT. We also included a group of MH-susceptible volunteers to examine any similarities in gene expression that might define common underlying molecular defects between the two disorders, and their responses to exertional heat stress. We aimed to explore the possibility of using differential gene expression as a biomarker for the risk of EHI, MH susceptibility, or both.The details of the subjects from the first phase of recruitment and their HTT data have been published previously . Those oThis analysis compared differences in gene expression in blood samples taken prior to heat tolerance testing and included five healthy controls, all passing the HTT, six EHI cases, one of whom failed the HTT and six MH susceptible individuals, one of whom failed the HTT.Relative to control samples, 291 genes (153 upregulated/138 downregulated) were differentially expressed in the EHI cohort. Enrichment analysis of upregulated genes highlighted increased activity in the “Interferon Gamma Response”, “TNF-alpha Signalling via NF-kB” and “Inflammatory Response” hallmarks A. SeveraA greater divergence in transcriptome profile was observed in the MHS cohort featuring 1019 genes differentially expressed compared to controls (575 upregulated/444 downregulated). Upregulated genes were significantly enriched in ‘TGF-beta Signalling’, ‘Mitotic Spindle’ and ‘UV Response Dn’ hallmarks D, with oTo identify similarities between both conditions a Venn diagram was created comparing both ‘EHI vs. Control’ and ‘MHS vs. Control’ baseline gene sets A. EHI ann = 6), MHS (n = 6) and control (n = 5) samples. No significant interaction effect between phenotype (EHI/MH/control) and HTT timepoints was observed. Phenotype groups were subsequently combined for simple timepoint analysis revealing 5074 genes differentially expressed at 2 h vs. baseline and 7079 genes differentially expressed at 24 h vs. 2 h. Genes upregulated (2682) at the 2 h timepoint were mainly associated with the ‘TNF-α Signalling via NF-κB’ and ‘Inflammatory Response’ hallmarks, whilst downregulated genes (2392) were associated mainly with Myc and mTORC1 signalling. At 24 h, the effects on gene expression appear to normalize as the ‘TNF-α Signalling via NF-κB’ and ‘Inflammatory Response’ hallmarks are downregulated with Myc and mTORC1 signalling hallmarks upregulated, respectively  using EHI (ectively . The genn = 10) with those who failed . The variability between batches was accounted for by incorporating a batch term within the DESeq2 design model. Between-group comparisons at each time point showed few differences (BTNL3 downregulated in EHI-FAIL), and only four genes were found across the 2 h timepoint .Due to limitations in the initial sample set, a second analysis was performed after recruiting additional EHI samples from individuals who failed the HTT (baseline and 2 h). This allowed us to further compare EHI individuals who passed the HTT  revealed 1586 (1227 upregulated/359 downregulated) and 3203 genes (2030 upregulated/1173 downregulated) differentially expressed in EHI-PASS and EHI-FAIL responses respectively. All the genes found in the EHI-PASS and EHI-FAIL responses were cross-compared using a Venn diagram which showed a large crossover, accounting for 87.1% of the EHI PASS response  B. HoweveSubsequent enrichment analysis of upregulated genes showed associations with ‘TNF-alpha Signalling via NF-kB’, ‘PI3K/AKT/mTOR Signalling’, ‘IL-6/JAK/STAT3 Signalling’ and ‘Apoptosis’, all of which were also enriched in the normal 2 h HTT response previously described C. EnrichMHS and EHI baseline comparisons reveal dysregulated gene expression in metabolic pathways and immune response pathways. Comparisons of EHI and MHS samples with controls at baseline, along with responses shared between EHI and MHS samples, indicate increased expression of genes involved in responses to IFNγ and TNFα via NFΚB signalling, as hallmarks of a pro-inflammatory response. Although interestingly, the MHS versus control analysis also highlighted increased expression of genes associated with TGFβ signalling, typically regulating the pro-inflammatory response. In theory, specific genes of interest upregulated in EHI individuals might be detected by a simple blood test. However, the level of up-regulation and gene profile overlapping with other conditions would compromise sensitivity and specificity.Differentially expressed genes associated with pro-inflammatory response pathways were expressed up to four-fold higher in subjects with EHI, compared to healthy controls at rest. Dysregulation of the inflammation pathway is not surprising as it is widely accepted that EHI, which advances to EHS triggers a systematic inflammatory response, which can lead to multi-organ failure and death in extreme cases ,11. HoweTogether with the upregulated pro-inflammatory hallmarks in EHI subjects at baseline, the gene ontology analysis revealed biological processes associated with the maintenance of telomeres to be downregulated. Telomerase-related genes, involved in the maintenance of telomeres with roles in cell cycle control and aging/cell death are also involved in multiple pathways including immune response pathways relevant to the pro-inflammatory response ,13. MoleIn addition to gene expression in immune response pathways, we observed decreased expression of MYC target genes involved in cell proliferation, including mitochondrial biogenesis, but also apoptosis . Throughp = 0.021) but lower flux control ratios in ‘Complex I + Complex II (OXPHOS)’ and ‘Complex II (ETS)’ of mitochondria from MH susceptible individuals compared with control  showing that human MH susceptible mitochondria have a functional deficiency [2+ regulation and mitochondria [Genes associated with OXPHOS were downregulated most prominently in MH susceptible patients, although there also appears to be some effect in those with a history of EHI. Ontology results surrounding mitochondrial function had an emphasis on Complex I NADH dehydrogenase, the first component of the electron transport chain. Previously we have used high-resolution respirometry to compare oxygen consumption rates (oxygen flux) between permeabilised human MH susceptible and control skeletal muscle fibres. Baseline comparisons showed significantly increased mitochondrial mass  used a different study design where six individuals with a history of EHS and 18 controls were subjected to both an HTT and a thermoneutral test (on separate days) with blood collected before and immediately post-testing for genome-wide microarray analysis . For eacIn summary, we have found differences in basal whole blood gene expression in patients susceptible to MH or with a history of EHI compared to controls, including an increase in pro-inflammatory gene expression and a decrease in expression of genes associated with OXPHOS, adipogenesis and myoblast proliferation. The HTT triggered gene expression changes in the same pathways observed in the baseline data, but these changes were more pronounced in those who failed the HTT, featuring a greater number of differentially expressed genes. We speculate that the elevated pro-inflammatory gene expression at baseline pre-disposes individuals to excessive inflammatory events under duress, resulting in episodes of EHI. There is potential for this to be used as a screening tool for EHI but more research is required to increase the specificity for this condition.RYR1 gene, and had a positive IVCT with 0.5 g contracture at 2% v/v halothane and a 0.2 g contracture at 2 mmol L−1 caffeine. An additional EHI volunteer was recruited due to technical issues obtaining core temperature and sweat measurements from a member of the original EHI group.All subjects were male, aged 18–40 years old, with a good base level of fitness. Recruitment and sample analysis took place in two phases. The first set of samples was composed of six members of the armed forces who had presented with EHI (EHI group), six healthy military personnel with no history of EHI (control group) and six MHS patients from the Leeds MH cohort MHS group. The MHS group was age, sex and fitness-matched to the military volunteers. The EHI recruits demonstrate a range of phenotypes, including collapse, loss of consciousness and hyperthermia. Individuals recruited into the MHS group were either MH index cases or family members, who all carried a pathogenic variant in the The second sample set was collected because only one member of the original EHI group demonstrated an inability to thermoregulate in the HTT and there was interest in comparing the gene expression profiles of EHI subjects who had failed the HTT (Inability to thermoregulate) with EHI subjects who had passed the HTT (demonstrated thermoregulation). We, therefore, recruited further military personnel who had presented with EHI, five who passed the HTT and nine who failed the HTT. Subject characteristics for this cohort are supplied in All volunteers underwent the same standardised HTT , carried® Blood RNA tubes  at three time points  for the first phase but only baseline and 2 h for the second phase. The samples were stored at −20 °C prior to transfer to the Leeds MH Investigation Unit to be processed.Blood samples for global gene expression analysis were collected into PAXgene® Blood RNA kits  according to the manufacturer’s instructions. Each RNA sample was washed, purified, and treated with DNase 1 prior to storage at −80 °C. Purified RNA samples were quantified and quality checked using Agilent’s RNA ScreenTape assay and 2200 TapeStation instrument  according to the manufacturer’s instructions. RNA samples with integrity scores of RINe > 7.0 were classed as good quality and acceptable for further use.RNA was extracted from the whole blood samples using PAXgeneTM RNA BR Assay Kit  before being used to create libraries using the Truseq Stranded mRNA library preparation kit , according to the manufacturer’s guidelines. All cDNA libraries were quality-checked using the Agilent D1000 ScreenTape  and quantified using the Quant-iTTM PicoGreen® dsDNA assay .Poly (A)-selected mRNA libraries were created from the isolated RNA by the Next Generation Sequencing (NGS) Facility at St James’s Hospital, Leeds. RNA samples were first quantified using the Qubit® 3000 platform , according to the manufacturer’s instructions. The 150 bp paired-end reads were de-multiplexed to produce a forward and reverse Fastq file for each sample, on each lane. The RNA sequencing for both runs was performed by the Leeds University NGS facility, located at St James’s University Hospital, Leeds. The average read depths from the first sample set (n = 51) and a second set (n = 28) of samples were 36.8 M and 25 M reads per sample, respectively.Equimolar concentrations of each mRNA-enriched cDNA library were pooled and sequenced across lanes of Illumina’s HiSeqThe ‘ssizeRNA’ package in R was used to calculate a basic estimation of the sample size required to reach a power of 0.8 . This esFastq files for each technical replicate were combined and trimmed using Cutadapt  before thttps://appyters.maayanlab.cloud; accessed on 15 September 23) [Functional annotation of differentially expressed genes was achieved using Enrichr ,44. Initmber 23) .p-value < 0.05, adjusted for multiple testing using the Benjamini–Hochberg (BH) adjustment [q-value < 0.05.Differentially expressed genes generated by DESeq2 are defined using a threshold of adjusted justment . Signifi


We hypothesized that a gas-free ultrasound contrast agent can be incorporated into blood clots at a concentration that does not affect the tPA-mediated clot dissolution rate, while enabling quantitative assessment of the clot dissolution rate. Clots were formed from a mixture of whole rabbit blood, 1 M calcium chloride, human thrombin and varying amounts of microcrystalline cellulose. Washed clots in tubes were weighed at 30, 60 and 90 minutes after addition of recombinant tPA (rtPA) in porcine plasma (100 μg/ml). Clot echogenicity at each time point was assessed using a Philips HDI 5000 ultrasound system using an L12-5 linear array probe. Recorded Images underwent videodensitometric analysis that converted image reflectivity to mean gray scale values (MGSV). We found that 1.12 mg/ml of microcrystalline cellulose in rabbit blood clots (0.2 ml) provided optimal echogenicity without affecting clot dissolution rates (0.3-0.6 mg/min.) caused by rtPA. The clot dissolution rate measured by videodensitometric analysis of the echogenic clots agreed well with that determined by mass loss measurements . This method will be important for demonstrating  Ischemic stroke is the most common acute neurologic illness. Stroke-related costs in the United States came to nearly $53 billion between 2017 and 20182. The introduction of recombinant tissue plasminogen activator  as a clinical thrombolytic agent for acute ischemic stroke (AIS) 25 years ago was a breakthrough in the treatment of strokes caused by clots in the carotid and cerebral arteries 5. However, free tPA’s hemorrhagic side effects and the difficulty treating clots in the carotid and cerebral arteries have limited the usefulness of free tPA in treating acute ischemic stroke 8. Ultrasound has been found to improve the effectiveness of rtPA, but hemorrhagic side effects, which can be fatal, continue to limit optimization of the protocols 9. Because rtPA produces low rates of complete recanalization and increased rates of symptomatic intracerebral hemorrhage (ICH), only 2-5% of acute ischemic stroke patients in the United States are given intravenous rtPA treatment 13. The use of intracranial Doppler ultrasound treatment as an adjunct to intravenous rtPA was shown to increase recanalization  within 2 hours of rtPA administration in acute ischemic stroke patients in the CLOTBUST study 14. However, the improved recanalization did not persist, as indicated by neurological outcome 3 months after treatment .Stroke ranks second as a cause of death worldwide and third as a cause of lost disability-adjusted life-years in high-income countries. In the United States, 87% of strokes are caused by focal cerebral ischemia due to arterial occlusion (ischemic stroke),16. In addition, we have successfully loaded rtPA into these carriers, creating an ultrasound-controlled thrombolytic drug-delivery nanotechnology 17. TELIP’s thrombolytic activity is comparable to that of free tPA and is enhanced by both continuous wave and pulsed Doppler ultrasound 19. A preliminary in vivo study using a rabbit aorta clot model demonstrated that Doppler ultrasound enhances TELIP thrombolysis significantly in 15 minutes 20. A follow-up study using this model showed that TELIP has the thrombolytic efficacy of locally delivered rtPA 21. This formulation may overcome the longtime problems of tPA treatment of acute ischemic stroke and significantly improve thrombolytic therapy by combining the self-targeting TELIP construct with ultrasound tPA activity enhancement22.We have developed a novel therapeutic carrier, intrinsically echogenic liposomes (ELIP), that can serve not only their original purpose as an ultrasound contrast agent, but also as a vehicle for ultrasound-triggered controlled drug release 23. Treatment efficacy is evaluated by in situ measurement of thrombus dissolution rate and middle cerebral artery (MCA) flow rate, as well as behavioral measures of stroke recovery and brain infarct volume. The original study employed radiolabeled thrombi monitored by quantitative scintigraphic analysis. Magnetic resonance imaging (MRI) is currently the method of choice for monitoring the rate of in vivo thrombus dissolution in real time, but requires specialized instrumentation and experienced investigators.An appropriate approach to establishing the thrombolytic efficacy of TELIP, with and without transcranial pulsed Doppler ultrasound, relative to free rtPA in the treatment of acute ischemic stroke would be to test it in a rabbit embolic stroke model. This model was used to optimize rtPA therapy for acute ischemic stroke three decades ago To devise a method for monitoring thrombus dissolution that is relatively simple and inexpensive, while avoiding the use of radioactive materials, we aimed to demonstrate the feasibility of monitoring clot dissolution rates using quantitative ultrasound imaging techniques. This was accomplished by videodensitometric analysis of ultrasound contrast agent-impregnated clot sonograms at various times. This method has the additional advantage of utilizing the same equipment required to insonify the thrombus during TELIP administration.Clots were formed in 1.5 ml Eppendorf tubes  by mixing 100 μl whole rabbit blood with 25 μl 1 M calcium chloride, 50 μl 0.02 M phosphate-buffered saline, pH 7.4 (PBS), and 25 μl thrombin (2.5 U), and incubating at 37° C for 2-18 hours. Varying concentrations  of recombinant tissue plasminogen activator  in 500 μl porcine plasma (as a source of plasminogen) was added to pre-weighed clots; replicate (3X) clots were washed with PBS and weighed with an OHAUS analytical balance  at 30, 60 and 90 minutes after addition of rtPA. The rtPA concentration giving the best linear clot dissolution rate over 90 minutes was chosen for subsequent studies.25. Varying volumes (10-30 μl) of a 7.5 mg/ml MCC suspension in water were added during clot formation, with reduction of the PBS volume by a corresponding amount. Clot echogenicity at each time point was assessed with a Philips HDI 5000 ultrasound system using an L12-5 linear array probe 21 positioned laterally to tubes placed in an anechoic chamber. Videodensitometric analysis was performed. Alteplase (100 μg/ml)-mediated clot mass loss rates were determined as described above.The echogenicity of microcrystalline cellulose  suspensions was confirmed by intravascular ultrasound (IVUS). Recorded images were subjected to videodensitometric analysis that converted image reflectivity to mean gray scale values (MGSV) as previously described Clot echogenicity loss was measured as MGSV decrease and % reduction (using 0.225 mg MCC/clot), which was compared with the clot mass loss rate.Linear regressions, including fit equations and variance analyses of the individual points, were performed with SigmaPlot 10.0 software .Of the rtPA concentrations added to clots in 500 ml porcine plasma, 100 μg/ml provided the best linear dissolution rate , which wTwo repetitions of the dissolution curve with 100 μg/ml rtPA exhibited good linearity and were nearly parallel . DiffereAddition of varying amounts of the stock microcrystalline cellulose (MCC) suspension, up to 30 μl (0.225 mg) per clot, allowed clot dissolution rates similar to undoped clots . AdditioWhen clot mass loss and MGSV data were converted to percent clot reduction as a means of comparison, serial videodensitometric measurements of tPA-treated clots yielded dissolution rates at 60 and 90 minutes that were very similar to those found by clot mass loss determinations .The dissolution rate measurements of clot mass loss by each method were similar. Divergence was noted below 60 minutes for both measurements. This may indicate increased variability at earlier stages of the clot dissolution process.In this study, we have shown that a) a soluble ultrasound contrast agent  can be incorporated into blood clots without affecting the rate of tPA-induced mass loss; b) the MCC-doped clots can be visualized by conventional ultrasound imaging methods; c) tPA-induced clot dissolution can be monitored quantitatively by videodensitometric techniques; and d) clot dissolution rates determined by US monitoring are similar to those determined by clot mass loss measurements. Thus, we have created a method for monitoring tPA-induced thrombus dissolution suitable for real-time measurements in a rabbit thrombotic stroke model.27. This may be due to improved diffusion that promotes transport of drugs into the thrombus, reformation and opening of the fibrin matrix that enhances drug diffusion, clearing of fibrin polymers that increases the surface for drug interaction, or direct effects on binding of the agent to fibrin 28. Ultrasound produces cavitation, which allows large molecules and particles to penetrate cells (sonoporation) 29, and this property is actively being investigated for drug and gene delivery 34. Addition of a contrast agent into a carrier as an ultrasound nucleation agent can lower the threshold for these ultrasound bioeffects 36.Clinical studies have demonstrated that use of focused ultrasound plus a thrombolytic agent improves thrombolysis for stroke and acute myocardial infarction in vitro and in vivo19. In a preliminary study using a rabbit aorta thrombolysis model, we showed complete recanalization 15 minutes after TELIP administration in rabbits receiving 5.7 MHz pulsed Doppler ultrasound (MI = 0.43) vs. 60% mean recanalization in rabbits receiving TELIP only 20. A follow-up study, comparing TELIP to established clinical thrombolytic protocols, established that TELIP was at least as effective as free rtPA, with and without Definity cavitation, in terms of maximum percent recanalization within a 30-minute period and rate of total recanalization 24. Pulsed ultrasound was used in that study to extend previously observed thrombolytic potentiation from continuous wave ultrasound to clinically relevant conditions.We have demonstrated that clinical Doppler US increases TELIP thrombolysis, both 23 provided the basis for optimization of rtPA protocols for clinical ischemic stroke therapy 37. We have demonstrated the efficacy of TELIP in a rabbit abdominal aorta thrombus model, but a demonstration of both efficacy and safety in a stroke model is a necessary next step in preclinical development of the formulation. The larger vessel size in rabbits should provide a better projection of clinical TELIP efficacy than commonly used rat embolic stroke models, although rat ischemic stroke models have been sufficient to demonstrate free tPA efficacy39.The Zivin rabbit stroke model 37. Such a study would provide information needed to extend these findings to identify safety and efficacy of our novel therapeutic carrier, to define our ability to utilize ultrasound as a therapeutic adjunct for improved thrombolysis without increasing cerebral hemorrhage, and to perform baseline trials allowing the TELIP formulation and protocol to be extended into the clinical arena.In addition, this rabbit thrombotic stroke model was used to establish the kind of safety and efficacy information that is required for translational product development and was shown to be clinically relevant in vivo, preferably in Zivin’s rabbit thrombotic stroke model. Such validation will add a convenient, relatively inexpensive option to the currently employed radiotracer and MRI methodologies.To that end, we have demonstrated in this study that ultrasound imaging can be employed quantitatively to monitor clot mass loss in real time during plasminogen activator-induced thrombolysis. This method must now be validated We have devised a method of monitoring thrombolytic-induced clot mass loss by ultrasound imaging using a non-gas containing contrast agent introduced into the thrombus and have shown that dissolution rates in the presence of tPA measured by this method agreed with rates determined by clot mass loss measurements. This method will be useful in determining the efficacy of nanoparticulate tPA formulations in rabbit ischemic stroke models where MRI measurement is not available.


Using high-dimensional, multiplexed flow cytometry, we profile and compare the CSF and peripheral blood mononuclear cell (PBMCs) immune populations between patients with LMD and those without. Patients with LMD observe a lower overall frequency of CD45+ cells , lower frequencies of CD8+ T cells , and higher frequency of Tregs than patients without LMD. Interestingly, the frequency of partially exhausted CD8+ T cells (CD38hiTIM3lo) is ~6.5-fold higher among patients with LMD vs. those without . Taken together, these data suggest that patients with LMD may have lower overall immune infiltrates than patients without LMD, suggesting a more permissive CSF immune microenvironment but a higher frequency of partially exhausted CD8+ T cells, which may offer an important therapeutic target.Leptomeningeal disease (LMD) is a devastating complication of metastatic breast cancer (MBC). In this non-therapeutic study, we enrolled 12 patients with MBC and known or suspected LMD who were undergoing a lumbar puncture as part of clinical care and collected extra cerebrospinal fluid (CSF) and a paired blood sample from each patient at a single time point. Of the 12 patients, 7 patients are confirmed to have LMD based on positive cytology and/or convincing MRI imaging (LMD The prognosis after the diagnosis of LMD is poor, with a median survival of 2–6 months, a statistic that has not changed significantly in over 20 years of published data4. More recently, there are reports of longer survival in patients with certain breast cancer subtypes with LMD, including those with HER2 positive MBC in which treatment with intrathecal (IT) HER2-directed therapies such as trastuzumab has resulted in median survival of closer to 12 months6. Patients with LMD are often excluded from clinical trials, and there are few effective treatments2. Therefore, it is important to better characterize the biology of this condition to develop better diagnostic and treatment modalities.Patients with metastatic breast cancer (MBC) can develop metastases to the leptomeninges and subarachnoid space surrounding the brain and spinal cord, a condition known as a leptomeningeal disease (LMD). Approximately 5–10% of patients with MBC develop LMD during the course of their disease, causing significant morbidity and mortality7. However, it is now well-established that immune cells are present in the brain and cerebrospinal fluid (CSF)9. There have been recent efforts to characterize the CSF immune profile in patients with LMD across tumor types. For example, in a study of patients with metastatic melanoma and CNS disease, Smalley et al. performed single-cell RNA sequencing on brain metastases and CSF samples and demonstrated that patients with LMD had a CSF microenvironment characterized by an immune-suppressed T-cell landscape distinct from that of brain and skin metastases8. In a study of patients with solid tumor malignancies and LMD receiving intravenous (IV) immune checkpoint inhibitors (ICIs), Prakadan et al. evaluated the CSF immune profiles before and after IV ICI treatment and found progressive CD8+ T cell abundance within the CSF9.Historically, it was thought that the central nervous system (CNS) is an immune-privileged site, an organ that is relatively isolated from the influences of the immune system+ T cells are exposed to persistent antigenic stimulation that leads to a dysfunctional state called “exhaustion,” which in turn leads to attenuated effector function and failure to control tumor progression12. A major goal of cancer immunotherapy is to reinvigorate exhausted and dysfunctional T cells to improve anti-cancer response. While the aforementioned studies described some characteristics of the CSF immune profiles of patients with LMD, the number of breast cancer patients in these studies was limited, and no published study to our knowledge has evaluated the exhaustion states of T cells in the CSF of patients with MBC and LMD.In addition to understanding the types of CSF immune cells, it is also important to characterize their functional state. Tumor-specific CD814 and the combination of IV nivolumab and ipilimumab15 in patients with solid tumor malignancies and LMD. However, it is unknown whether there is adequate CNS penetration of these agents, and it is possible that intrathecal (IT) administration may be superior. Therefore, IT ICI therapy has been proposed, with reports of using IT nivolumab17 and IT pembrolizumab18. However, efficacy in these studies is relatively limited, and understanding the immune milieu in the CSF is likely to provide important insights about how to improve these therapies for patients with CNS disease based on targeted hypotheses.Understanding the CSF immune profile may have therapeutic implications. For example, there has been recent interest in whether IV ICI therapy has CNS activity. Several studies evaluated the efficacy of IV pembrolizumab19 (LMDpos), and 5 patients were deemed not to have LMD based on similar criteria (LMDneg). Using a high-dimensional, multiplexed flow cytometric screen to profile immune cell populations, we evaluated the immune cell profiles in the CSF and peripheral blood mononuclear cell (PBMC) samples and compared the immune cell landscape between patients with LMD (LMDpos) versus those without LMD (LMDneg).In this non-therapeutic study, we enrolled 12 patients with MBC and known or suspected LMD who were undergoing a lumbar puncture (LP) as part of clinical care and collected extra CSF and a paired blood sample from each patient at a single time point; there were no restrictions on breast cancer subtype or lines of prior therapies in this pragmatic study. Of the 12 patients, 7 patients were ultimately confirmed to have LMD based on positive CSF cytology and/or convincing MRI imagingpos), and 5 patients did not have LMD based on similar criteria (LMDneg). Demographic characteristics, tumor characteristics, treatment history, and CNS involvement details are shown in Table Twelve patients with MBC and known or suspected LMD were enrolled in this study: 7 patients were ultimately confirmed to have LMD based on positive CSF cytology and/or convincing MRI imaging  between groups  cells was ~3-fold higher in LMDpos compared to LMDneg . Overall, we noted big differences in the immune landscape of LMDpos. Specifically, CD38+ expression on CD8+ T cells was observed to be higher than LMDneg in the CSF. These initial findings led us to investigate the relationship between each exhaustion marker in T cells between groups.To profile the CSF and PBMC immune microenvironments, we utilized high dimensional flow cytometry using a marker panel that included a broad array of immune cell markersups Fig. , b. Next23. Given the advantage of our high-dimensional marker panel to assess immune cell populations and uncover multiparametric features, we performed an unsupervised dimensionality reduction analysis to obtain a more detailed assessment of immune subsets present in the CSF of patients with and without LMD. Dimensionality reduction (UMAP) and hierarchical clustering identified 16 populations of cell phenotypes  were ~6.5-fold higher among LMDpos vs. LMDneg   (data not shown). Finally, the frequency of nonclassical monocytes expressing HLA-DR+CD163hi was ~3.4-fold lower in LMDpos vs. LMDneg  Fig.  or non-e+ cells, CD8+ T cells, CD4+ T cells, or myeloid cells between patients with LMD vs. those without  between groups  was significantly lower in LMDpos vs. LMDneg  that were enriched. Given that this population did not express high levels of PD-1 or LAG3, we characterized these as partially exhausted22. It is possible that targeting these T cells may be a strategy for improving immunogenicity against malignant cells in the CSF, although further functional studies are needed to clarify the functional role of these cells and to characterize how these and other T cell clusters in the CSF and PBMC fraction evolve over time. Taken together, these findings have potential therapeutic implications, as a major principle of action of cancer immunotherapy with immune checkpoint inhibitors is to reinvigorate exhausted and/or dysfunctional T cells32, so it may be possible to use ICI or other therapies to reinvigorate these cells and provide therapeutic benefit.Conventional markers of T cell exhaustion are PD-1, TIM3, and LAG3pos vs. LMDneg. While it is still unknown, we hypothesize that these circulating monocytes play a critical role in influencing the tumor microenvironment, specifically T cell exhaustion states. Previous studies reported that CD163 expression might be a prognostic biomarker and predictor of overall survival in patients with colorectal cancer34 and is also correlated with response to neoadjuvant chemotherapy in patients with early stage breast cancer35. In a mouse model of breast cancer, the onset of T cell exhaustion was linked to TAM abundance, and TAMs forming long-lasting synapses with CD8+ T cells further primes T cell exhaustion36. Taken together, the relationship between our identified population of CD163+ monocytes and TAMs in the CSF would need to be better characterized in future studies.Circulating monocytes are a major source of tumor-associated macrophages (TAMs) in breast cancer. In addition to differences seen in T cell populations, we also observed differences in a population of monocytes that expressed HLA-DR and CD163 that was less abundant in both the CSF and PBMC samples of LMD22. In addition, single-cell omic approaches could support the validation and expansion of these findings38.There are several important limitations of this work. First, to maximize CSF acquisition, this study included flexible inclusion criteria, allowing patients with any hormone and HER2 receptor subtype and without limitation on prior or current treatment history, including several patients with LMD who had received prior IT therapy. Despite these flexible inclusion criteria, there was a relatively similar distribution of breast cancer receptor subtypes and similar median overall lines of therapy among patients with LMD vs. those without LMD that were included in this analysis. Second, we only collected CSF specimens at a single time point in this study, given that many of these patients did not live long enough for serial sampling; in the future, we will attempt to collect serial samples in a subset of patients if possible. Third, immune cell profiles were analyzed by high dimensional flow cytometry using a select panel of markers, which may not fully capture the immune cell diversity. Future studies could expand the total number of markers to include additional functional markers like effector vs. naïve markers, interferon-gamma, and others+ and CD8+ T cells and a higher frequency of Treg than patients without LMD, suggesting a more permissive immune environment and a higher frequency of partially exhausted CD8+ T cells (CD38hiTIM3lo). Larger studies are needed to validate these findings and determine whether there are prognostic or predictive features of the CSF immune cell profile which may have clinical utility. If one or more of these immune signatures is validated in a larger cohort, it is possible that it could serve as a biomarker to promote early detection, provide prognostic information, and inform treatment decisions for patients with MBC and LMD.In conclusion, these data indicate that patients with MBC and LMD had a lower overall frequency of CD45Male or female patients ≥18 years who had histologically confirmed MBC with known or suspected LMD based on either radiographic or clinical findings and who were undergoing an LP for clinical care were eligible to enroll in this non-therapeutic study to collect extra CSF for research purposes. The study was approved by the University of California San Francisco (UCSF) Comprehensive Cancer Center Protocol Review Committee on Human Research, and written informed consent was obtained from all patients prior to trial enrollment. We also consented to five healthy controls who donated blood for research purposes to verify known immune cell populations in the PMBC fraction; these healthy controls were enrolled by the UCSF Immunoprofiler Initiative under a UCSF IRB-approved protocol.19.The diagnosis of LMD was based on positive CSF cytology and/or convincing MRI imaging using standard criteria for the diagnosis of LMDDetailed information about patient demographic characteristics, tumor histology, sites of metastatic involvement, treatment history, and survival status were obtained via manual chart extraction from the electronic medical record.CSF was extracted via an LP or tap of an Ommaya reservoir as part of clinical care. An extra 6–10cc of CSF was collected for this study into EDTA tubes , stored on ice, and processed within 3 h of sample collection. CSF was spun at 1500 rpm for 15 min at 4 °C, and the supernatant was aspirated to collect the cell pellet for flow staining. CSF cell count and diff indicated scant red blood cell contamination (0–5 RBCs) in the CSF specimens, so red blood cell lysis protocol was not utilized for CSF specimens.A 5–10cc of serum was collected into EDTA tubes at the same time as the CSF fluid extraction, stored on ice, and processed within 3 hours of sample collection. Whole blood was prepared by treatment of 1 ml of peripheral blood with red blood cell lysis buffer  according to the manufacturer’s instructions. PBMCs were then processed further for flow staining.After cell isolation, CSF and PBMCs were stained with live/dead Aqua (Thermo #L23105) in phosphate buffer saline (PBS) for 15 min at 4 °C in the dark. After FACS  buffer washes, cells were incubated with Human FcX (Biolegend #422302) for 10 min to prevent non-specific antibody binding. Following the Fc block, cells were stained with a master mix of CD45 BD Bio #612891; CD3 Biolegend #344852; CD4 Biolegend #344658; CD8 BD Bio #740411; CD14 BD Bio #740773; CD16 BD Bio #612944; CD19 antibodies.com a18909; CD38 BD Bio #564979; CD1c Biolegend #331516; BDCA3 BD Bio #565084; CD123 Invitrogen 62-1239-42; CD11c BD Bio #747459; CD197 Biolegend #353208; HLA-DR BD Bio #564040; PD-1 BD Bio #563789; CD127 BD Bio #563225; CD25 Invitrogen #15-0259-42; CD163 Biolegend #333610; CD223 Invitrogen #46-2239-42; CD366 Invitrogen #12-3109-42; CD56 Biolegend #392428; HER2 Biolegend #324412; CD169 Biolegend #346016. Cells were then washed and analyzed on the Cytek Aurora  high dimensional flow cytometry machine. Our marker panel is also shown in Supplementary Fig. +. A UMAP algorithm for dimensionality reduction was then applied using FloJo UMAP plugin (v3.1) for KNN = 30. Computational analysis was carried out on FlowSOM (v3.0.18) to delineate the total number of clusters generated, followed by ClusterExplorer (v1.6.5) and Morpheus (Broad Institute) for cell cluster annotations. All frequencies of clusters in bar plots delineated are calculated by dividing cluster “x” over all clusters. Hierarchical clustering was generated by one minus Pearson correlation on rows and columns, and expressions are transformed by subtracting row mean, divided by row standard deviation.All CSF or PBMC samples were analyzed by FloJo (v10.7.1), batch-corrected using CytoNorm (v1.2.3) from FloJo plugins, and concatenated to create a single, 100,000-cell composite file. In this composite file, cells were pre-gated as follows: singlets, live, and CD45t-tests between groups for coarse assessment of immune populations. Frequency bar plots for comparing multiple clusters from UMAP between patients with or without LMD were generated by performing one-way ANOVA followed by the Tukey post hoc test. All data on specific statistical tests and resulting significance levels can be found in each figure legend. Data collection and analysis of immune profiles from groups were performed blind until endpoint validation by clinical chart information. All figures were generated with GraphPad Prism and curated in Adobe Illustrator.All data were analyzed using Prism Software . Descriptive statistics were used to summarize numeric responses as the rate of events (%), median , or mean ± standard error mean as appropriate. The time to onset of metastases, time to LMD diagnosis and survival distributions was estimated by the Kaplan–Meier non-parametric method. Frequency bar plot statistics were performed by unpaired This research was approved by the UCSF Institutional Review Board.Supplementary Figures


Synechocystis sp. PCC 6803, and we integrated this information with transcriptomic data. Across all conditions, daily EPS productivity of individual cells was highest in the early growth phase, but the total amount of EPS obtained from the cultures was highest in the later growth phases due to accumulation. Lowering the magnesium concentration in the media enhanced per-cell productivity but the produced EPS had a lower total sugar content. Levels of individual monosaccharides correlated with specific culture media components, e.g. xylose with sulfur, glucose and N-acetyl-galactosamine with NaCl. Comparison with RNA sequencing data suggests a Wzy-dependent biosynthetic pathway and a protective role for xylose-rich EPS. This multi-level analysis offers a handle to link individual genes to the dynamic modulation of a complex biopolymer.Microorganisms produce extracellular polymeric substances  of diverse composition and structure. The biochemical and biophysical properties of these biopolymers enable a wide range of industrial applications. EPS from cyanobacteria are particularly versatile as they incorporate a larger number and variety of building blocks and adopt more complex structures than EPS from other organisms. However, the genetic makeup and regulation of EPS biosynthetic pathways in cyanobacteria are poorly understood. Here, we measured the effect of changing culture media on titre and composition of EPS released by Synechocystis exopolysaccharide amount and composition depends on culture condition• Production rate and sugar content can be modulated by Mg and S respectively• Wzy-dependent biosynthetic pathway and protective role proposed for xylose-rich EPS• The online version contains supplementary material available at 10.1007/s00253-023-12697-9. Extracellular polymeric substances  are complex glycans secreted by various microorganisms including bacteria, microalgae and fungi , branching and linkage types  transporter-, and synthase-dependent pathways  in different growth phases of the cultures and we confirmed that they were not toxic for mammalian cells. In the second part of the study, we compared RPS production of cultures grown in different media  and we integrated the data with previously obtained transcriptomics data for the same conditions. This multi-level analysis revealed novel correlations between environment, EPS sugar usage and genes, thus offering a basis for manipulating EPS composition in a model cyanobacterium.EPS production often increases under stress. It is likely that, under conditions that limit biomass production, EPS synthesis provides a sink for excess electrons and photosynthetically assimilated carbon. For example, EPS production in several cyanobacterial strains was reported to increase under nutrient limitation   in a Lambda 45 UV/VIS Spectrophotometer . To ensure measurements were performed in the linear range of the spectrophotometer, cultures were diluted in fresh media to OD <1, the sample OD was measured, and the culture OD was calculated by multiplying the sample OD with the respective dilution factor.EPS harvest was performed at various times during culture growth to reflect different growth phases: 1) “early” at the beginning of rapid growth phase after initial lag phase, 2) “late” at the end of the rapid growth phase when culture growth slows down due to emerging limitations, and 3) “stationary” when culture density no longer increased, or decreased. The harvest days to reflect these phases were decided for each culture based on preliminary growth curves and regular OD measurements during growth. ODs at harvest varied because growth differed between cultures and conditions. At the end of the experiment only those samples that could be assigned to one of the three growth phases were included in the analysis. Details on harvest days and ODs are provided in supplemental Table g for 10 min at 4 °C. The supernatant was vacuum filtered through a 1.2 μm cellulose ester filter  and subsequently dialysed in 8 kDa cellulose dialysis tubing  against ELGA water (1:10) for 48 h with five water changes and constant slow stirring. The dialysed product was lyophilised at -60 °C and below 20 mTor pressure using a VirTis sentry 2.0 freeze dryer . Dry RPS samples were weighed, and this value was used to determine RPS production rates. Water-soluble RPS stocks were suspended at 10 mg/ml in ELGA water and insoluble precipitates were removed by centrifugation at 8000 g for 2 min at 21 °C.For RPS harvest, supernatant of cultures was collected by centrifugation at 4000 OD is the culture density as optical density at 730 nm, D is the culture age in days, and n represents day of OD measurement. This equation approximates the area under the growth curve with the sum of areas of rectangles where one side is time between OD measurements and the other side is the linear average of two consecutively measured ODs. In an alternative approach we tried to fit established growth models (e.g. Gompertz) to the measured ODs to calculate integrals. However, goodness of fits varied between cultures, and we therefore decided to use Equation 1 as the simplest approximation for all cultures based on the measured OD values.The area under the growth curve (AUGC) was used to normalise RPS production titres to the total number of cells that were available for production up to the time point of harvest. It was calculated using Eq. 1:2SO4 as reference  assay with bovine serum albumin (BSA) as reference (Thermo Fisher Scientific). Carbohydrate concentration was determined using the phenol-sulfuric acid method with glucose as reference  and 300 °C splitless injection of 1 μl samples. References were included for each of the reported monosaccharides (Sigma-Aldrich).High-performance liquid chromatography (HPLC) - size exclusion chromatography (SEC) was performed using an Alliance 2695 HPLC system equipped with a Shodex SB806M aqueous GFC column (Shodex) and refractive index detector  with dextran and heparin as references (Sigma-Aldrich). The mobile phase was 0.1 mM EDTA, 5 mM Tris pH 7, 0.09% NaCl at a flow rate of 0.5 ml/min.Synechocystis spp. PCC 6803 cultures grown in control (BG11) and five nutrient limited conditions  in three biological replicates (independently grown cultures). Data are presented as fragments per kilobase of gene per million reads mapped (FPKM). Significant differences between conditions and time points were determined using Cuffdiff , BG11 with low (12.5%) concentrations of N, K, P, Mg or S  and removing insoluble particulate matter. EPS are complex polymers comprised of a sugar backbone decorated with various non-sugar components such as acidic and anionic side groups, proteins and DNA  to total sugar and xylose content, respectively. The gene lists (with associated Pearson correlation and transcriptomic data) can be found in Table The modularity of EPS biosynthetic pathways offers opportunities for bioengineering bespoke polymers , including the Wzx flippase, which provide a good starting point for targeted knockout analyses.Biosynthetic pathways can be engineered to decouple product synthesis from other cellular processes, e.g. growth or stress response (Burg et al. To conclude; this study provides insights into how environmental conditions, notably culture media, can be used to control EPS production and composition in a cyanobacterium and further proposes a new EPS biosynthesis pathway. Characterisation of more EPS features in more environmental conditions, paired with “omics and knockout analyses,” will generate a more detailed picture of EPS biosynthesis, its regulation and the machinery involved. This knowledge base will improve industrial production and enable approaches using both random and carefully selected combinations of EPS production machinery to generate polymers with new and exciting properties for industry.