Biomedical subjects

Ramit Mehr

Publications and source records attributed to Ramit Mehr.

5 recordsLinked to original sources

PubMed2003

Models for antigen receptor gene rearrangement. III. Heavy and light chain allelic exclusion.

The extent of allelic exclusion in Ig genes is very high, although not absolute. Thus far, it has not been clearly established whether rapid selection of the developing B cell as soon as it has achieved the first productively rearranged, functional heavy chain is the only mechanism responsible for allelic exclusion. Our computational models of Ag receptor gene rearrangement in B lymphocytes are hereby extended to calculate the expected fractions of heavy chain allelically included newly generated B cells as a function of the probability of heavy chain pairing with the surrogate light chain, and the probability that the cell would test this pairing immediately after the first rearrangement. The expected fractions for most values of these probabilities significantly exceed the levels of allelic inclusion in peripheral B cells, implying that in most cases productive rearrangement and subsequent cell surface expression of one allele of the heavy chain gene probably leads to prevention of rearrangement completion on the other allele, and that additional mechanisms, such as peripheral selection disfavoring cells with two productively rearranged heavy chain genes, may also play a role. Furthermore, we revisit light chain allelic exclusion by utilizing the first (to our knowledge) computational model which addresses and enumerates B cells maturing with two productively rearranged kappa light chain genes. We show that, assuming that there are no selection mechanisms responsible for abolishing cells expressing two light chains, the repertoire of newly generated B lymphocytes exiting the bone marrow must contain a significant fraction of such kappa double-productive B cells.

Alleles↗

PubMed2003

Generation of the natural killer cell repertoire: the sequential vs. the two-step selection model.

Natural killer (NK) cells are lymphocytes which can kill tumor and virus-infected cells, and mediate acute rejection of bone marrow grafts. NK-cell killing is directed primarily at target cells which do not express sufficient levels of self-major histocompatibility complex (MHC) class-I molecules. Inhibition of lysis of self-MHC-expressing target cells is mediated via inhibitory receptors on the NK cell, which bind to MHC molecules. Each NK cell expresses only a subset of all its inhibitory receptor gene repertoire, which may bind to only a subset of the self-MHC molecules expressed by other cells of the organism. Two conceptual models have been proposed to explain the process of NK cell 'education' in which these cells adapt, during their development, to the self-MHC environment: the two-step selection and the sequential models. In this manuscript we develop mathematical and computational models of the process of NK cell development and education, which implement the two conceptual models. We use this theoretical framework to examine the available data on NK cell repertoire compositions, and evaluate the degree these data support either of the two conceptual models. We show that the data published so far on NK cell receptor expression patterns is insufficient to refute either model, since data on NK cell receptor binding affinities to MHC is also needed. However, the models allow us to make predictions on these binding affinities, which can later be tested experimentally.

Animals↗

PubMed2003

Asynchronous differentiation models explain bone marrow labeling kinetics and predict reflux between the pre- and immature B cell pools.

B lymphopoiesis has historically been depicted as a unidirectional process, in which cohorts of developing cells transit through successive differentiative stages in an irreversible, synchronous manner. Here, we examine this view by combining kinetic analysis of developing B cell subsets in the bone marrow with mathematical modeling. Our bromo-deoxyuridine (BrdU) labeling data are incompatible with B cell development being a synchronous process, because labeling curves are non-linear. Moreover, we show that B cell development may not be completely unidirectional, because our results support the possibility of a phenotypic "reflux" among the immature to the pre-B cell subsets.

Animals↗

PubMed2002

Age- and tissue-specific differences in human germinal center B cell selection revealed by analysis of IgVH gene hypermutation and lineage trees.

The elderly produce increased levels of antibodies to autologous antigens and are less able to make high-affinity antibodies to foreign antigens. Ig gene hypermutation is integral to the affinity maturation process but previous studies of hypermutation with age have yielded conflicting results. The cells studied have represented post-germinal center (GC) populations and, therefore, the results may be complicated by possible differences in activation history. We studied Ig genes from GC B cells to elucidate which factors in the affinity maturation process change with age. Age-related changes in the pattern of hypermutation were seen, although the analysis of variable region heavy chain (VH) genes and their lineage trees shows that an alteration in the mechanism of somatic hypermutation is unlikely. The changes are due to founder cell effects and/or the process of selection. Striking tissue-specific differences were seen. All measurements indicated that selection of Ig genes may decrease in Peyer's patch GC but increase in splenic GC with age. These tissue-specific differences highlight the importance of considering the activation and effector sites when studying immune senescence.

Aging↗

PubMed2002

PESI--an intelligent system for prediction of enzyme-substrate interactions based on experimental constraints.

We present a system for predicting protein-protein modifications, and demonstrate its usefulness in the field of signal transduction research. Signal transduction is one of the most important areas of investigation in biological research. One of the major mechanisms frequently employed by cells to regulate signal transduction processes involves protein phosphorylation by various kinases. As many as 1,000 protein kinases and 500 protein phosphatases in the human genome are thought to be involved in phosphorylation processes which regulate all aspects of cell function. The complexity of such interactions stems from the enormous number of factors and interactions, which makes the identification of putative substrates for any given enzyme by straightforward experimentation increasingly difficult. We present here a data mining algorithm, based on the similarity between the modifier proteins and between the modified proteins, and on experimental constraints. The application presented here (PESI) focuses on substrate phosphorylation by various enzymes. This algorithm reduces the number of substrate candidates for experimental study by about two orders of magnitude. Moreover, this algorithm has already yielded predictions for previously unknown substrates of the enzymes PKCdelta and PKCeta, which we have confirmed experimentally.

Algorithms↗