Increased Immune-Regulatory Receptor Expression on Effector T Cells as Early Indicators of Relapse Following Autologous Stem Cell Transplantation for Multiple Myeloma.

The benefit of autologous stem cell transplantation (ASCT) in newly diagnosed myeloma patients, apart from supporting high dose chemotherapy, may include effects on T cell function in the bone marrow (BM). We report our exploratory findings on marrow infiltrating T cells early post-ASCT (day+100), examining phenotype and T cell receptor (TCR) repertoire, seeking correlations with timing of relapse. Compared to healthy donors (HD), we observed an increase in regulatory T cells (CD4+FoxP3+, Tregs) with reduction in CD4 T cells, leading to lower CD4:8 ratios. Compared to paired pre-treatment marrow, both CD4 and CD8 compartments showed a reduction in naïve, and increase in effector memory subsets, suggestive of a more differentiated phenotype. This was supported by increased levels of several immune-regulatory and activation proteins (ICOS, PD-1, LAG-3, CTLA-4 and GzmB) when compared with HD. Unsupervised analysis identified a patient subgroup with shorter PFS (p=0.031) whose BM contained increased Tregs, and higher immune-regulatory markers (ICOS, PD-1, LAG-3) on effector T cells. Using single feature analysis, higher frequencies of marrow PD-1+ on CD4+FoxP3- cells and Ki67+ on CD8 cells were independently associated with early relapse. Finally, studying paired pre-treatment and post-ASCT BM (n=5), we note reduced abundance of TCR sequences at day+100, with a greater proportion of expanded sequences indicating a more focused persistent TCR repertoire. Our findings indicate that, following induction chemotherapy and ASCT, marrow T cells demonstrate increased activation and differentiation, with TCR repertoire focusing. Pending confirmation in larger series, higher levels of immune-regulatory proteins on T cell effectors at day+100 may indicate early relapse.

Marrow-Infiltrating Regulatory T Cells Correlate with the Presence of Dysfunctional CD4+PD-1+ Cells and Inferior Survival in Patients with Newly Diagnosed Multiple Myeloma.

PURPOSE: Immune dysregulation is described in multiple myeloma. While preclinical models suggest a role for altered T-cell immunity in disease progression, the contribution of immune dysfunction to clinical outcomes remains unclear. We aimed to characterize marrow-infiltrating T cells in newly diagnosed patients and explore associations with outcomes of first-line therapy. EXPERIMENTAL DESIGN: We undertook detailed characterization of T cells from bone marrow (BM) samples, focusing on immune checkpoints and features of immune dysfunction, correlating with clinical features and progression-free survival. RESULTS: We found that patients with multiple myeloma had greater abundance of BM regulatory T cells (Tregs) which, in turn, expressed higher levels of the activation marker CD25 compared with healthy donors. Patients with higher frequencies of Tregs had shorter PFS and a distinct Treg immune checkpoint profile (increased PD-1, LAG-3) compared with patients with lower frequencies of Tregs. Analysis of CD4 and CD8 effectors revealed that low CD4effector (CD4eff):Treg ratio and increased frequency of PD-1-expressing CD4eff cells were independent predictors of early relapse over and above conventional risk factors, such as genetic risk and depth of response. Ex vivo functional analysis and RNA sequencing revealed that CD4 and CD8 cells from patients with greater abundance of CD4effPD-1+ cells displayed transcriptional and secretory features of dysfunction. CONCLUSIONS: BM-infiltrating T-cell subsets, specifically Tregs and PD-1-expressing CD4 effectors, negatively influence clinical outcomes in newly diagnosed patients. Pending confirmation in larger cohorts and further mechanistic work, these immune parameters may inform new risk models, and present potential targets for immunotherapeutic strategies.

Measuring Microbial Mutation Rates with the Fluctuation Assay.

Fluctuation assays are widely used for estimating mutation rates in microbes growing in liquid environments. Many cultures are each inoculated with a few thousand cells, each sensitive to a selective marker that can be assayed phenotypically. These parallel cultures grow for many generations in the absence of the phenotypic marker. A subset of cultures is used to estimate the total number of cells at risk of mutations (i.e., the population size at the end of the growth period, or Nt). The remaining cultures are plated onto the selective agar. The distribution of observed resistant mutants among parallel cultures is then used to estimate the expected number of mutational events, m, using a mathematical model. Dividing m by Nt gives the estimate of the mutation rate per locus per generation. The assay has three critical aspects: the chosen phenotypic marker, the chosen volume of parallel cultures, and ensuring that the surface on the selective agar is completely dry before the incubation. The assay is relatively inexpensive and only needs standard laboratory equipment. It is also less laborious than alternative approaches, such as mutation accumulation and single-cell assays. The assay works on organisms that go through many generations rapidly and it depends on assumptions about the fitness effects of markers and cell death. However, recently developed tools and theoretical studies mean these issues can now be addressed analytically. The assay allows mutation rate estimation of different phenotypic markers in cells with different genotypes growing in isolation or in a community. By conducting multiple assays in parallel, assays can be used to study how an organism's environmental context affects spontaneous mutation rate, which is crucial for understanding antimicrobial resistance, carcinogenesis, aging, and evolution.

Unraveling the Excited-State Dynamics of Eosin Y Photosensitizers Using Single-Molecule Spectroscopy.

The intersystem crossing and dispersive electron-transfer dynamics of eosin Y (EY) photosensitizers are probed using single-molecule microscopy. The blinking dynamics of EY on glass are quantified by constructing cumulative distribution functions of emissive ("on") and nonemissive ("off") events. Maximum likelihood estimation (MLE) and goodness-of-fit tests based on the Kolmogorov-Smirnov (KS) statistic are used to establish the best fit to the blinking data and differentiate among competitive photophysical processes. The on-time probability distributions for EY in N2 and air are power-law distributed after ∼1 s, with fit parameters that are significantly modified upon exposure to oxygen. By extending the statistically principled MLE/KS approach to include an onset time for log-normal behavior, we demonstrate that the off-time distribution for EY in N2 is best fit to a combination of exponential and log-normal functions. The corresponding distribution for EY in air is best fit to a log-normal function alone. Furthermore, power law and log-normal distributions are observed for an individual molecule in air, consistent with dynamic fluctuations in the rate constant for dark-state population and depopulation. These observations support the interpretation that dispersive electron transfer (i.e., the Albery model) from the first excited singlet state (S1) of EY to trap states on glass is predominately responsible for blinking in oxic conditions. In anoxic environment, both triplet-state blinking and dispersive electron transfer from S1 and the excited triplet state (T1) contribute to the excited-state dynamics of EY.

Opposing effects of final population density and stress on Escherichia coli mutation rate.

Evolution depends on mutations. For an individual genotype, the rate at which mutations arise is known to increase with various stressors (stress-induced mutagenesis-SIM) and decrease at high final population density (density-associated mutation-rate plasticity-DAMP). We hypothesised that these two forms of mutation-rate plasticity would have opposing effects across a nutrient gradient. Here we test this hypothesis, culturing Escherichia coli in increasingly rich media. We distinguish an increase in mutation rate with added nutrients through SIM (dependent on error-prone polymerases Pol IV and Pol V) and an opposing effect of DAMP (dependent on MutT, which removes oxidised G nucleotides). The combination of DAMP and SIM results in a mutation rate minimum at intermediate nutrient levels (which can support 7 × 108 cells ml-1). These findings demonstrate a strikingly close and nuanced relationship of ecological factors-stress and population density-with mutation, the fuel of all evolution.

Spontaneous mutation rate is a plastic trait associated with population density across domains of life.

Rates of random, spontaneous mutation can vary plastically, dependent upon the environment. Such plasticity affects evolutionary trajectories and may be adaptive. We recently identified an inverse plastic association between mutation rate and population density at 1 locus in 1 species of bacterium. It is unknown how widespread this association is, whether it varies among organisms, and what molecular mechanisms of mutagenesis or repair are required for this mutation-rate plasticity. Here, we address all 3 questions. We identify a strong negative association between mutation rate and population density across 70 years of published literature, comprising hundreds of mutation rates estimated using phenotypic markers of mutation (fluctuation tests) from all domains of life and viruses. We test this relationship experimentally, determining that there is indeed density-associated mutation-rate plasticity (DAMP) at multiple loci in both eukaryotes and bacteria, with up to 23-fold lower mutation rates at higher population densities. We find that the degree of plasticity varies, even among closely related organisms. Nonetheless, in each domain tested, DAMP requires proteins scavenging the mutagenic oxidised nucleotide 8-oxo-dGTP. This implies that phenotypic markers give a more precise view of mutation rate than previously believed: having accounted for other known factors affecting mutation rate, controlling for population density can reduce variation in mutation-rate estimates by 93%. Widespread DAMP, which we manipulate genetically in disparate organisms, also provides a novel trait to use in the fight against the evolution of antimicrobial resistance. Such a prevalent environmental association and conserved mechanism suggest that mutation has varied plastically with population density since the early origins of life.