***TASK***
the task is to simplify the input abstract of a biomedical literature

***INPUT***
the input is the abstract of a biomedical literature

***OUTPUT***
the output is the simplified abstract for the input abstract of a biomedical literature
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Input: Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.
Output:  When species evolve, their genes duplicate and diverge to allow for adaptation of their functional repertoires to the changing environment. In this scenario, unrelated genes can convergently evolve to produce proteins with the same molecular function, termed “functionally analogous.” A quantitative determination of the reaction similarities among functionally analogous enzymes could provide insight about the different structural solutions nature has used to evolve similar catalysts. Bond changes between substrates and products, and between successive reaction intermediates, were used to compare the reactions catalyzed and the mechanisms of catalysis for 95 pairs of functionally analogous enzymes. Less than half of the reactions catalyzed by unrelated enzymes, but defined as similar by the Enzyme Commission (EC) classification, are similar in terms of bond changes, suggesting that this classification often fails to capture quantitative differences between many enzyme reactions. Furthermore, we addressed for the first time whether the chemical mechanisms by which similar overall reactions are achieved in functional analogs are also similar. We conclude that convergence of reaction is often accompanied by convergence of chemical mechanism. These results will be useful for classifying enzymes, guiding functional annotation of newly determined enzyme sequences and structures and for informing the engineering of enzymes with new functions.

Input:  In recent years, highly detailed characterization of adult bone marrow (BM) myeloid progenitors has been achieved and, as a result, the impact of somatic defects on different hematopoietic lineage fate decisions can be precisely determined. Fetal liver (FL) hematopoietic progenitor cells (HPCs) are poorly characterized in comparison, potentially hindering the study of the impact of genetic alterations on midgestation hematopoiesis. Numerous disorders, for example infant acute leukemias, have in utero origins and their study would therefore benefit from the ability to isolate highly purified progenitor subsets. We previously demonstrated that a Runx1 distal promoter (P1)-GFP::proximal promoter (P2)-hCD4 dual-reporter mouse (Mus musculus) model can be used to identify adult BM progenitor subsets with distinct lineage preferences. In this study, we undertook the characterization of the expression of Runx1-P1-GFP and P2-hCD4 in FL. Expression of P2-hCD4 in the FL immunophenotypic Megakaryocyte-Erythroid Progenitor (MEP) and Common Myeloid Progenitor (CMP) compartments corresponded to increased granulocytic/monocytic/megakaryocytic and decreased erythroid specification. Moreover, Runx1-P2-hCD4 expression correlated with several endogenous cell surface markers’ expression, including CD31 and CD45, providing a new strategy for prospective identification of highly purified fetal myeloid progenitors in transgenic mouse models. We utilized this methodology to compare the impact of the deletion of either total RUNX1 or RUNX1C alone and to determine the fetal HPCs lineages most substantially affected. This new prospective identification of FL progenitors therefore raises the prospect of identifying the underlying gene networks responsible with greater precision than previously possible.


Output:

The production of red blood cells, platelet-producing megakaryocytes, and immune response-directing granulocytes and monocytes is initiated at an early stage in the developing embryo and continues throughout life. The proportion of each cell type varies depending on the specific needs of the organism. We know that in the mouse embryo, specialized blood progenitor cells emerge in the fetal liver and produce mature blood cells in response to different cues. However, it is difficult to distinguish between red blood cell and white blood cell-producing progenitors with sufficiently high accuracy to study these cues. For example, we know that several childhood blood disorders, such as leukemias, are caused by genetic mutations in blood progenitor cells before birth, but studying the effects of these mutations in a mouse disease model is hampered if we don’t know which blood progenitor cells to collect. We have used different genetic markers to help distinguish red blood cell, megakaryocyte and granulocyte/monocyte-producing progenitor cells with a greater precision than was previously possible. Furthermore, to illustrate how this technique can be used to study blood disorders, we demonstrated that mutations affecting the transcription factor Runx1 impair the abilities of different progenitors to produce mature blood cells in different ways.
