The Evolving Microbiome of Dental Caries.

Dental caries is a significant oral and public health problem worldwide, especially in low-income populations. The risk of dental caries increases with frequent intake of dietary carbohydrates, including sugars, leading to increased acidity and disruption of the symbiotic diverse and complex microbial community of health. Excess acid production leads to a dysbiotic shift in the bacterial biofilm composition, demineralization of tooth structure, and cavities. Highly acidic and acid-tolerant species associated with caries include Streptococcus mutans, Lactobacillus, Actinomyces, Bifidobacterium, and Scardovia species. The differences in microbiotas depend on tooth site, extent of carious lesions, and rate of disease progression. Metagenomics and metatranscriptomics not only reveal the structure and genetic potential of the caries-associated microbiome, but, more importantly, capture the genetic makeup of the metabolically active microbiome in lesion sites. Due to its multifactorial nature, caries has been difficult to prevent. The use of topical fluoride has had a significant impact on reducing caries in clinical settings, but the approach is costly; the results are less sustainable for high-caries-risk individuals, especially children. Developing treatment regimens that specifically target S. mutans and other acidogenic bacteria, such as using nanoparticles, show promise in altering the cariogenic microbiome, thereby combatting the disease.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study.

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK.

MinimuMM-seq: Genome Sequencing of Circulating Tumor Cells for Minimally Invasive Molecular Characterization of Multiple Myeloma Pathology.

Multiple myeloma (MM) develops from well-defined precursor stages; however, invasive bone marrow (BM) biopsy limits screening and monitoring strategies for patients. We enumerated circulating tumor cells (CTC) from 261 patients (84 monoclonal gammopathy of undetermined significance, 155 smoldering multiple myeloma, and 22 MM), with neoplastic cells detected in 84%. We developed a novel approach, MinimuMM-seq, which enables the detection of translocations and copy-number abnormalities through whole-genome sequencing of highly pure CTCs. Application to CTCs in a cohort of 51 patients, 24 with paired BM, was able to detect 100% of clinically reported BM biopsy events and could replace molecular cytogenetics for diagnostic yield and risk classification. Longitudinal sampling of CTCs in 8 patients revealed major clones could be tracked in the blood, with clonal evolution and shifting dynamics of subclones over time. Our findings provide proof of concept that CTC detection and genomic profiling could be used clinically for monitoring and managing disease in MM. SIGNIFICANCE: In this study, we established an approach enabling the enumeration and sequencing of CTCs to replace standard molecular cytogenetics. CTCs harbored the same pathognomonic MM abnormalities as BM plasma cells. Longitudinal sampling of serial CTCs was able to track clonal dynamics over time and detect the emergence of high-risk genetic subclones. This article is highlighted in the In This Issue feature, p. 247.

The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action.

The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.

Autoregulation of the Streptococcus mutans SloR Metalloregulator Is Constitutive and Driven by an Independent Promoter.

Streptococcus mutans, one of ∼600 bacterial species in the human oral cavity, is among the most acidogenic constituents of the plaque biofilm. Considered to be the primary causative agent of dental caries, S. mutans harbors a 25-kDa SloR metalloregulatory protein which controls metal ion transport across the bacterial cell membrane to maintain essential metal ion homeostasis. The expression of SloR derives in part from transcriptional readthrough of the sloABC operon, which encodes a Mn2+/Fe2+ ABC transport system. Here we describe the details of the sloABC promoter that drives this transcription as well as those for a novel independent promoter in an intergenic region (IGR) that contributes to downstream sloR expression. Reverse transcriptase PCR (RT-PCR) studies support the occurrence of sloR transcription that is independent of sloABC expression, and the results of 5' rapid amplification of cDNA ends (5' RACE) revealed a sloR transcription start site in the IGR, from which the -10 and -35 promoter regions were predicted. The results of gel mobility shift assays support direct SloR binding to the IGR, albeit with a lower affinity than that for SloR binding to the sloABCR promoter. The function of the sloR promoter was validated by semiquantitative real-time PCR (qRT-PCR) experiments. Interestingly, sloR expression was not significantly affected when bacteria were grown in the presence of a high manganese concentration, whereas expression of the sloABC operon was repressed under these conditions. The results of in vitro transcription studies support the occurrence of SloR-mediated transcriptional activation of sloR and repression of sloABC Taken together, these findings implicate SloR as a bifunctional regulator that represses sloABC promoter activity and encourages sloR transcription from an independent promoter.IMPORTANCE Tooth decay is a ubiquitous infectious disease that is especially pervasive in underserved communities worldwide. S. mutans-induced carious lesions cause functional, physical, and/or esthetic impairment in the vast majority of adults and in 60 to 90% of schoolchildren in industrialized countries. Billions of dollars are spent annually on caries treatment, and productivity losses due to absenteeism from the workplace are significant. Research aimed at alleviating S. mutans-induced tooth decay is important because it can address the socioeconomic disparity that is associated with dental cavities and improve overall general health, which is inextricably linked to oral health. Research focused on the S. mutans SloR metalloregulatory protein can guide the development of novel therapeutics and thus alleviate the burden of dental cavities.