Serum protein profiling reveals mechanism of activated thrombus formation in patients with stroke and atrial fibrillation.

Stroke is an acute cerebrovascular disease in which blood flow to the brain is suddenly disrupted, causing damage to nerve cells. It involves complex and diverse pathophysiological processes and the treatment strategies are also diverse. The treatment for patients with stroke and atrial fibrillation (AF) is aimed at suppressing thrombus formation and migration. However, information regarding the protein networking involved in different thrombus formation pathways in patients with AF and stroke is insufficient. We performed protein profiling of patients with ischemic stroke with and without AF to investigate the mechanisms of thrombus formation and its pathophysiological association while providing helpful information for treating and managing patients with AF. These two groups were compared to identify the protein networks related to thrombus formation in AF. We observed that patients with ischemic stroke and AF had activated inflammatory responses induced by C-reactive protein, lipopolysaccharide-binding protein, and alpha-1-acid glycoprotein 1. In contrast, thyroid hormones were increased due to a decrease in transthyretin and retinol-binding protein 4 levels. The mechanism underlying enhanced cardiac activity, vasodilation, and the resulting thrombosis pathway were confirmed in AF. These findings will play an essential role in improving the prevention and treatment of AF-related stroke.

Uncovering the health implications of abandoned mines through protein profiling of local residents.

Residents in areas with abandoned mines risk significant exposure to abundant heavy metals in the environment. However, current clinical indicators cannot fully reflect the health changes associated with abandoned mine exposure. The aim of this study was to identify biological changes in the residents of abandoned mine areas via proteomic analysis of their blood. Blood samples were collected from abandoned mine and control areas, and mass spectrometry was used for protein profiling. A total of 138 unique or common proteins that were differentially expressed in low-exposure abandoned mine area (LoAMA) or high-exposure abandoned mine area (HiAMA) compared to non-exposure control area (NEA) were analyzed, and identified 4 clusters based on functional similarity. Among the 10 proteins that showed specific change in LoAMA, 4 proteins(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) were cluded in cluster 1(plasma lipoprotein remodeling), and linked to proteins that showed specific change in protein expression in HiAMA. Therefore, it is suggested that 4 proteins are changed at low exposure to an abandoned mine (or initial exposure), and then at high exposure, changes in various proteins involved in linked plasma lipoprotein remodeling are induced, which might triggered by the 4 proteins. Interestingly, in addition to plasma lipoprotein remodeling, proteins involved in other functional networks were changed in the high exposure group. These were all directly or indirectly linked to the 4 biomarkers(Apolipoprotein M, Apolipoprotein E, Apolipoprotein L1, and Cholesteryl ester transfer protein) that changed during low exposure. This suggests their potential utility in identifying areas impacted by abandoned mines. Especially, proteins involved in lipid metabolism and renal function-related diseases in individuals exposed to heavy metals in abandoned mine areas were correlated. Chronic kidney disease is predominantly instigated by cardiovascular disease and is commonly accompanied by dyslipidemia.

Cadmium-associated protein changes in residents of contaminated areas: Abandoned mine and smelter.

Cadmium (Cd), a serious environmental contaminant, is associated with adverse health effects. However, the specific changes that the human body experiences in response to exposure to varying concentrations of cadmium remain unknown. The high levels of heavy metal contamination, especially Cd, in abandoned mines and smelter sites make them ideal locations to investigate the physiological manifestations of Cd exposure. This study found that individuals inhabiting abandoned mine and smelter areas had higher concentrations of Cd in their urine and blood compared to those living outside these areas (i.e., the controls). Furthermore, proteomic profiling of blood samples from all study groups was performed to identify proteomic biomarkers associated with chronic and severe Cd exposure. This analysis showed statistically significant correlations between urine Cd levels and sixteen proteins. Among these proteins, seven exhibited significantly altered expressions in samples from contaminated areas compared with those from control areas. Therefore, these proteins were selected as potential markers representing Cd-related protein alterations. Multiple reaction monitoring analysis was performed to validate the expression patterns of the proteins and four proteins were found to exhibit consistent trends. The findings show that Cd exposure significantly affects the expression of certain proteins in the human body. Understanding the underlying mechanisms and diseases associated with Cd-induced protein alterations can aid in the development of effective preventive and therapeutic strategies for individuals exposed to Cd-linked pollution.

Discovery and validation of protein biomarkers for monitoring the effectiveness of drug treatment for major depressive disorder.

Major depressive disorder (MDD) has a high prevalence worldwide. Although the economic burden of depression increases annually, the proportion of patients with MDD receiving treatment did not increase between 2010 and 2018, suggesting an unmet treatment need. The burden of long-term treatment for depression is borne by patients. In this context, biomarkers associated with drug-treatment responses can be used as reference indicators to reduce unnecessary treatment and costs. Changes in biomolecules in response to drug treatment for depression and drug-treatment response markers have been studied extensively. The Hamilton Depression Rating Scale (HAM-D) is mainly used as an indicator of response and remission; however, it is difficult to determine whether the medication contributes to recovery when evaluating the effect of drug treatment for depression based on this assessment. Therefore, it is necessary to monitor the effect of medication compared to normal health conditions. Here, serum protein levels were compared using liquid chromatography-tandem mass spectrometry among a group of patients with depression who did not receive medication, a group of patients receiving medication, and a control group. Eight selected biomarkers, including Apolipoproteins A-I, Complement factor H, Complement C5, Complement C1q subcomponent subunit B, Alpha-2-HS-glycoprotein, Complement C1q subcomponent subunit C, Vitamin D-binding protein and Corticosteroid-binding globulin were distinguished between disease states, and protein levels in the drug-treated group were similar to those in the control group. These markers can be used to monitor the effectiveness of drug treatment.

Discovery and validation of a protein biomarker for the diagnosis and classification of disease severity of major depressive disorder.

BACKGROUND AND AIMS: Diagnosis and classification of disease severity of major depressive disorder (MDD) are determined through a doctor's consultation and questionnaire-based rating scale. This study aimed to identify and validate a serum protein biomarker for diagnosing and classifying the disease severity of MDD. MATERIALS AND METHODS: Based on the Hamilton Depression Rating Scale (HAMD) score, participants were divided into control, mild, moderate, and severe groups. Samples prepared from collected sera were analyzed using non-targeted qualitative and targeted quantitative tools to identify potential biomarkers. RESULTS: Four proteins were selected as biomarker candidates, which showed statistically significant consistent tendencies depending on MDD severity. Among them, tetranectin was the only validated protein in the quantitative analysis that showed the same decreasing tendency as that in the qualitative analysis. Furthermore, tetranectin showed fair discrimination performance between the control and MDD group. CONCLUSIONS: Tetranectin may be a novel potential biomarker for diagnosing and classifying the severity of MDD, though further verification and validation studies of its efficacy are needed.

Serum Protein Profiling Reveals a Decrease in Apolipoprotein A-IV During a Clinical Depressive Mood State.

Purpose: Depressive mood is a major psychiatric symptom that causes serious disturbances in daily life. Unlike physical symptoms, psychiatric symptoms are more difficult to evaluate objectively. Therefore, we aimed to discover biomarkers that reflect changes in serum protein metabolism during a clinical depressive mood. Methods: Serum protein profiling was conducted in participants who were not experiencing a current depressive episode (healthy individuals and patients in remission). Serum proteins were identified and quantified using liquid chromatography-tandem mass spectrometry. Differentially expressed proteins with a p-value <0.05 were selected, and candidate biomarkers were verified using multiple reaction monitoring analysis for absolute quantification. Results: Apolipoprotein A-IV levels were lower in the group with a current episode of depression than in the remission and healthy control groups. Further, fibronectin levels were also lower in the group with a current episode of depression than in the healthy control group but not in the remission group. Conclusion: We found that apolipoprotein A-IV-mediated inflammation is involved in clinical depressive moods, possibly by inducing neurological changes in the brain. Therefore, apolipoprotein A-IV and fibronectin levels may be explored as potentially novel biomarkers for detecting a current episode of depression.

Discovery and validation of metabolite markers in bloodstains for bloodstain age estimation.

Bloodstain age estimation involves measuring time-dependent changes in the levels of biomolecules in bloodstains. Although several studies have identified bloodstain metabolites as markers for estimating bloodstain age, none have considered sex, age-related metabolomic differences, or long-time bloodstain age. Therefore, we aimed to identify metabolite markers for estimating the age of bloodstains at weekly intervals within 28 days and validate them through multiple reaction monitoring. Adenosine 5'-monophosphate, choline, and pyroglutamic acid were selected as markers. Seven metabolites were validated, including five previously reported metabolites, ergothioneine, hypoxanthine, L-isoleucine, L-tryptophan, and pyroglutamic acid. Choline and hypoxanthine can be used to differentiate bloodstains between days 0 and 14 after deposition at weekly intervals, whereas L-isoleucine and L-tryptophan can help distinguish bloodstains between 7 days before and 14 days after deposition. Evaluation of the changes in metabolite levels according to sex and age revealed that the average levels of all seven metabolites were higher in women on day 0. Moreover, the level of ergothioneine was significantly higher in elderly individuals than in young individuals at all time points. In this study, we confirmed the potential effectiveness of metabolites in bloodstains as forensic markers and provided a new perspective on metabolomic approaches linked to forensic science.

Potential Biomarkers to Distinguish Type 1 Myocardial Infarction in Troponin-Elevated Diseases.

Classifying myocardial infarction by subtype is crucial for appropriate patient management. Although troponin is currently the most commonly used biomarker, it is not a specific marker for myocardial infarction and cannot distinguish subtypes. Furthermore, previous studies have confirmed that proteins known as myocardial infarction markers could function to distinguish the type of myocardial infarction. Therefore, we identify a marker that can distinguish type 1 myocardial infarction from other diseases with elevated troponin. We used mass spectrometry to compare type 1 myocardial infarction with other conditions characterized by troponin elevation and identified new candidate markers for disease classification. We then verified these markers, along with those already known to be associated with cardiovascular disease and plaque rupture. We identified α-1 acid glycoprotein 2, corticosteroid-binding globulin, and serotransferrin as potential distinguishing markers. The presence of these markers and other parameters, such as chest pain, electrocardiogram, and troponin levels from the complementary diagnostic processes, could provide valuable information to specifically diagnose type 1 myocardial infarction.

Internal standard metabolites for estimating origin blood volume of bloodstains.

The volume of blood leaked from blood vessels may change due to evaporation of water under the natural influence of the external environment. Bloodstains and dried blood spots (DBS), which describes blood dried in the external environment, are similar in their production and their metabolite quantification profiles. In both bloodstain metabolite analysis in the forensic science field and DBS metabolite analysis in the clinical field, it is important to determine the volume of the origin blood as this affects metabolite quantification results. Therefore, the purpose of this study is to discover the internal standard metabolites that have quantitatively proportional relationships with origin blood volume and maintain constant concentrations even as the age of the bloodstain increases. As a result, the concentrations of L-isoleucine and L-phenylalanine increased in proportion to the origin blood volume of the bloodstain. The differences in concentration of L-isoleucine were significant in all volume comparisons except in the comparison between 65 µL and 85 µL. The differences in concentration of L-phenylalanine were significant in all volume comparisons except between 65 µL and 45 µL and between 65 µL and 85 µL. In addition, it was confirmed that both metabolites tended to maintain constant concentrations without being affected by bloodstain age as the volume became smaller. These internal standard metabolites can be used for estimating the origin blood volume of bloodstains during metabolite analysis of bloodstains and DBS and could provide a volume criterion for standardization when comparing metabolite quantification between samples.

Effect of environmental conditions on bloodstain metabolite analysis.

Establishing a correlation between environmental variables and chemical change can significantly improve the quality of research in multiple fields. Among various environmental variables, temperature and humidity are closely related to the rate of chemical reactions. This study aimed to confirm changes in metabolite markers that were previously discovered in other temperature and humidity environment conditions and to confirm the possibility that they could act as markers. After blood collection from the subjects and bloodstain preparation, the quantitative values of the bloodstain metabolites were confirmed (when the age of the bloodstain was within a month) under eight environmental conditions (4 °C/30%, 4 °C/60%, 25 °C/30%, 25 °C/60%, 25 °C/90%, 40 °C/30%, 40 °C/60%, and 40 °C/90%). Age-of-bloodstain estimation models were constructed to confirm the applicability of bloodstain metabolites as markers for bloodstain age in various environments. The average concentration of metabolite markers exhibited a decreasing trend with the age of the bloodstain, which transformed into an increasing trend from day 7 onwards. In terms of temperature and humidity, 25 °C and 90%, respectively, showed the most dissimilar metabolite change pattern compared to other conditions. The age-of-bloodstain estimation models developed here have an R-square value of up to 0.92 for each condition and an R-square value of 0.71 when all environmental conditions were combined. The findings herein highlight the immense potential of blood metabolites for field application, confirming the possibility of predicting metabolite changes from the rates of their chemical reactions and validating the importance of metabolites as age-of-bloodstain markers under various environmental conditions.

Validation of the Metabolite Ergothioneine as a Forensic Marker in Bloodstains.

Ergothioneine, which is a naturally occurring metabolite, generally accumulates in tissues and cells subjected to oxidative stress, owing to its structural stability at physiological pH; therefore, it has been attracting attention in various biomedical fields. Ergothioneine has also been suggested as a potential forensic marker, but its applicability has not yet been quantitatively validated. In this study, quantitative analysis of ergothioneine in bloodstains was conducted to estimate the age of bloodstains and that of bloodstain donors. Blood from youth and elderly participants was used to generate bloodstains. After extracting metabolites from the bloodstains under prevalent age conditions, ergothioneine levels were quantified by mass spectrometry via multiple reaction monitoring. The concentration of ergothioneine in day 0 bloodstains (fresh blood), was significantly higher in the elderly group than in the youth group, but it did not differ by sex. Statistically significant differences were observed between the samples from the two age groups on days 0, 5 and 7, and on days 2 and 3 compared with day 0. The findings suggest that ergothioneine can be used to estimate the age of bloodstains and of the donor; it could be useful as a potential marker in reconstructing crime scenes.

Discovery and validation of acetyl-L-carnitine in serum for diagnosis of major depressive disorder and remission status through metabolomic approach.

Major depressive disorder (MDD) is one of the most common psychiatric disorders that accompany psychophysiological and mood changes. However, the pathophysiology-based disease mechanism of MDD is not yet fully understood, and diagnosis is also conducted through interviews with clinicians and patients. Diagnosis and treatment of MDD are limited due to the absence of biomarkers underlying the pathophysiological mechanisms of MDD. Although various attempts have been made to discover metabolite biomarkers for the diagnosis and treatment response of MDD, problems with sample size and consistency of results have limited clinical application. In addition, it was reported that future biomarker studies must consider exposure to antidepressants, which is the main cause of heterogeneity in depression subgroups. Therefore, the purpose of this study is to discover and validate biomarkers for the diagnosis of depression in consideration of exposure to drug treatment including antidepressants that contribute to the heterogeneity of the MDD subgroup. In the biomarker discovery and validation set, the disease group consisted of a mixture of patients exposed and unexposed to drug treatment including antidepressants for the treatment of MDD. The serum metabolites that differed between the MDD patients and the control group were profiled using mass spectrometry. The validation set including the remission group was used to verify the effectiveness as a biomarker for the diagnosis of depression and determination of remission status. The presence of different metabolites between the two groups was confirmed through serum metabolite profiling between the MDD patient group and the control group. Finally, Acetylcarnitine was selected as a biomarker. In validation, acetylcarnitine was significantly decreased in MDD and was distinguished from remission status. This study confirmed that the discovered acetylcarnitine has potential as a biomarker for diagnosing depression and determining remission status, regardless of exposure to drug treatment including antidepressants.

Bloodstain Metabolite Markers: Discovery and Validation for Estimating Age of Bloodstain within 7 Days.

Metabolomic research using analytical chemistry methods has been carried out in a wide range of research fields. However, research combining forensic science and metabolomics is rare. Determining the age of bloodstains could provide key information regarding when a crime was committed. Currently, validated methods for estimating the age of bloodstains are unavailable. Metabolites are intermediate and final products of chemical reactions. Therefore, they are less likely to be degraded than other components of blood under field conditions. In this study, metabolites in bloodstains were analyzed using liquid chromatography-mass spectrometry to discover and validate metabolic markers for determining the age of bloodstains within a week post-bleeding. Nontargeted analysis of bloodstain metabolites revealed statistically significant differences over time. Quantitative analysis of identified candidates via multiple reaction monitoring confirmed the statistical significance according to the age of bloodstain. Pyroglutamic acid, l-glutamine, acetylcarnitine, and adenosine 5'-monophosphate were selected as the final markers. The content of each marker exhibited a statistically significant and consistent tendency to decrease with the age of bloodstain. Furthermore, the effect of hemolysis was considered according to the blood fraction spots of the four markers. This study is the first to identify and validate metabolite markers that may help determine the age of bloodstains within a week post-bleeding. If applied to crime scenes as indicators of the age of bloodstains, they can be used as innovative and important tools for reconstructing crime scenes, suggesting initial investigative direction. This study highlights the forensic utility of blood metabolites ex vivo.

Hemoglobin subunit beta protein as a novel marker for time since deposition of bloodstains at crime scenes.

Dried bloodstains at crime scenes provide abundant information for analyzing criminal identity of victims or suspects, morphological characteristics, and biological and chemical compounds. Therefore, they are considered important evidence by investigators at crime scenes. Moreover, the age of bloodstains can be used to determine the timeline of incidents at crime scenes; Inappropriately handled bloodstains may cause degradation of blood components. In this study, we identified a novel marker, hemoglobin subunit beta protein, as an internal standard to determine the age of bloodstains at crime scenes. We found that the target spot between 20 and 30 kDa in two-dimensional electrophoresis gradually increased in size. The hemoglobin subunit beta protein was identified from this spot using liquid chromatography-tandem mass spectrometry and verified using western blotting. Sample bloodstains were exposed to various environmental conditions (humidity: 30%, 60%, 90% at room temperature [RT]). Furthermore, the hemoglobin subunit protein extracted from the sample bloodstains at various time points (0 h to 30 d) was dissolved in our newly developed buffer solution and in deionized or distilled water. We also analyzed the expression levels of the protein in the sample bloodstains, dried at RT and under various humidity over time, using western blotting. In addition, we evaluated the protein extraction capacity of deionized or distilled water and the newly developed buffer from the sample bloodstains over time. At RT and 60% humidity, using the newly developed buffer, the hemoglobin subunit beta protein levels showed a gradually increasing pattern. Finally, we quantitated human hemoglobin subunit beta protein using western blotting and enzyme-linked immunosorbent assay, which revealed significant differences among the samples. In particular, the time points from 36 h to 30 days were considered for analysis. Thus, the hemoglobin subunit beta protein dried at RT and 60% humidity and further dissolved in the newly developed buffer solution can be used to determine the age of bloodstains at crime scenes.

Discovery of donor age markers from bloodstain by LC-MS/MS using a metabolic approach.

Bloodstains are frequently encountered at crime scenes and they provide important evidence about the incident, such as information about the victim or suspect and the time of death or other events. Efforts have been made to identify the age of the bloodstain's donor through genomic approaches, but there are some limitations, such as the availability of databases and the quality dependence of DNA. There is a need for the development of a tool that can obtain information at once from a small blood sample. The aim of this study is to identify bloodstain metabolite candidates that can be used to determine donor age. We prepared bloodstain samples and analyzed metabolites using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Eighteen molecular features (MFs) were selected as candidates using volcano plots and multivariate analysis. Based on the MS/MS spectrum of the MFs, the following nine metabolites were identified from the METaboliteLINk database: Δ2-cis eicosenoic acid, ergothioneine, adenosine 5'-monophosphate, benzaldehyde, phenacylamine, myristic acid ethyl ester, p-coumaric acid, niacinamide, and N-arachidonoyl-L-alanine. These nine age markers at high or low abundances could be used to estimate the age of a bloodstain's donor. This study was the first to develop metabolite age markers that can be used to analyze crime scene bloodstains.

Serum proteomic analysis of major depressive disorder patients and their remission status: Novel biomarker set of zinc-alpha-2-glycoprotein and keratin type II cytoskeletal 1.

Major depressive disorder (MDD) is the most common mood disorder, and causes various mental, physical and cognitive symptoms. Clinicians diagnose MDD using multiple interviews and overall impression during the interviews, which makes MDD diagnosis highly subjective. To overcome this, we investigated novel protein biomarker for MDD. Serum from each subject were analyzed using nano liquid chromatography-triple time-of-flight mass spectrometry. We identified two proteins, zinc-alpha-2-glycoprotein (ZA2G) and keratin type II cytoskeletal 1 (K2C1), as final biomarkers. These biomarkers were downregulated during depression (p < 0.05, AUC of ROC >0.7). ZA2G is related to tryptophan metabolism, which is a main serotonin synthesis pathway. K2C1 is involved in the kinin-kallikrein system, which produces bradykinin, an anti-inflammatory mediator in the brain. Our results suggest that the two protein candidates are related to inflammation and that MDD is highly associated with inflammation. Finally, since all subjects in the two groups were taking antidepressants, our results suggest that the identified biomarkers could determine the presence or absence of illness and could be used to monitor therapeutic effects.

Serum biomarker discovery related to pathogenesis in acute coronary syndrome by proteomic approach.

Acute coronary syndrome (ACS) results from inadequate supply of blood flow from the coronary arteries to the heart or ischemia. ACS has an extremely high morbidity and mortality. The levels of biomarkers currently used for detection of ACS also increase in response to myocardial necrosis and other diseases and are not elevated immediately after symptoms appear, thus limiting their diagnostic capacity. Therefore, we aimed to discover new ACS diagnostic biomarkers with high sensitivity and specificity that are specifically related to ACS pathogenesis. Sera from 50 patients with ACS and healthy controls (discovery cohort) each were analyzed using mass spectrometry (MS) to identify differentially expressed proteins, and protein candidates were evaluated as ACS biomarkers in 120 people in each group (validation cohort). α-1-acid glycoprotein 1 (AGP1), complement C5 (C5), leucine-rich α-2-glycoprotein (LRG), and vitronectin (VN) were identified as biomarkers whose levels increase and gelsolin (GSN) as a biomarker whose levels decrease in patients with ACS. We concluded that these biomarkers are associated with the pathogenesis of ACS and can predict the onset of ACS prior to the appearance of necrotic biomarkers.

Discovery of Screening Biomarkers for Major Depressive Disorder in Remission by Proteomic Approach.

Major depressive disorder (MDD) is a common disorder involving depressive mood and decreased motivation. Due to its high heterogeneity, novel biomarkers are required to diagnose MDD. In this study, a proteomic method was used to identify a new MDD biomarker. Using sequential window acquisition of all theoretical mass spectra acquisitions and multiple reaction monitoring analysis via mass spectrometry, relative and absolute quantification of proteins in the sera was performed. The results of the relative quantitation by sequential window acquisition for all theoretical mass spectra data showed that seven proteins were significantly differently expressed between MDD patients and other patients with remission status. However, absolute quantification by multiple reaction monitoring analysis identified prothrombin as the only significantly upregulated protein in the depressive state compared to remission (p < 0.05) and was, thus, subsequently selected as an MDD biomarker. The area under the curve for prothrombin was 0.66. Additionally, increased prothrombin/thrombin induced hyper-activation of platelets via activating protease-activated receptors, a feature associated with MDD; specifically, activated platelets secrete various molecules related to MDD, including brain-derived neurotropic factors and serotonin. Therefore, prothrombin is a potential screening, prognostic, and diagnostic marker for MDD.

Biomarker Discovery of Acute Coronary Syndrome Using Proteomic Approach.

Acute coronary syndrome (ACS) is a condition in which the coronary artery supplying blood to the heart is infarcted via formation of a plaque and thrombus, resulting in abnormal blood supply and high mortality and morbidity. Therefore, the prompt and efficient diagnosis of ACS and the need for new ACS diagnostic biomarkers are important. In this study, we aimed to identify new ACS diagnostic biomarkers with high sensitivity and specificity using a proteomic approach. A discovery set with samples from 20 patients with ACS and 20 healthy controls was analyzed using mass spectrometry. Among the proteins identified, those showing a significant difference between each group were selected. Functional analysis of these proteins was conducted to confirm their association with functions in the diseased state. To determine ACS diagnostic biomarkers, standard peptides of the selected protein candidates from the discovery set were quantified, and these protein candidates were validated in a validation set consisting of the sera of 50 patients with ACS and 50 healthy controls. We showed that hemopexin, leucine-rich α-2-glycoprotein, and vitronectin levels were upregulated, whereas fibronectin level was downregulated, in patients with ACS. Thus, the use of these biomarkers may increase the accuracy of ACS diagnosis.

Microbial analyses of blood spot surfaces collected from a laboratory and the bathroom of a female single-person household under different environmental conditions.

Many people spend most of their time indoors, thereby exposing themselves to indoor environmental microbial communities that might interact with the human microbiota. These potential interactions have only been considered for personal identification; however, accumulating evidence indicates that these microbial interactions are potentially implicated with the identification of human interactions and location-specific factors including time and seasonal variations in the microbial community. To augment the potential of metagenomics-based forensic tools, we compared the composition of microbial communities in blood spot surfaces from healthy adults placed in different environments, such as in the bathroom of a female single-person household and on a laboratory, which were sampled across seasons and time points. The laboratory samples showed more changes in the bacterial community over time owing to the higher number of individuals using the laboratory, whereas the microbial communities in the bathroom samples remained relatively stable over time. Moreover, the two locations could be distinguished according to their specific bacterial community compositions. Variations were also observed related to changes in temperature and humidity, allowing for prediction of season-based microbial community. These findings offer a new perspective regarding the use of microbial community analysis in forensic science.