Biomedical subjects

Zemin Zhang

Publications and source records attributed to Zemin Zhang.

12 recordsLinked to original sources

PubMed2026

Multicellular ecosystems: Linking cellular diversity to tissue function and disease.

Tissue function emerges from coordinated interactions among diverse cell populations, whereas disruption of these interactions can lead to dysfunction. Recent advances in single-cell and spatial genomics have not only cataloged cellular diversity but also revealed how tissues are organized as dynamic multicellular ecosystems. Moving beyond descriptive cell atlases toward functional, system-level representations represents a major frontier in tissue biology. In this review, we outline conceptual and methodological frameworks for dissecting multicellular coordination, highlight recurrent multicellular ecosystems across physiological and pathological contexts, and explore translational opportunities such as patient stratification, therapeutic reprogramming, and regenerative strategies. Viewing tissues through an ecosystem lens provides a unifying framework that links cellular diversity to emergent tissue function and informs strategies for disease intervention.

Humans↗

PubMed2005

Maternal embryonic leucine zipper kinase/murine protein serine-threonine kinase 38 is a promising therapeutic target for multiple cancers.

To identify genes that could serve as targets for novel cancer therapeutics, we used a bioinformatic analysis of microarray data comparing gene expression between normal and tumor-derived primary human tissues. From this approach, we have found that maternal embryonic leucine zipper kinase (Melk), a member of the AMP serine/threonine kinase family, exhibits multiple features consistent with the potential utility of this gene as an anticancer target. An oligonucleotide microarray analysis of multiple human tumor samples and cell lines suggests that Melk expression is frequently elevated in cancer relative to normal tissues, a pattern confirmed by quantitative reverse transcription-PCR and Western blotting of selected primary tumor samples. In situ hybridization localized Melk expression to malignant epithelial cells in 96%, 23%, and 13% of colorectal, lung, and ovarian tissue tumor samples, respectively. Expression of this gene is also elevated in spontaneous tumors derived from the ApcMin and Apc1638N murine models of intestinal tumorigenesis. To begin addressing whether Melk is relevant for tumorigenesis, RNA interference-mediated silencing within human and murine tumor cell lines was done. We show that Melk knockdown decreases proliferation and anchorage-independent growth in vitro as well as tumor growth in a xenograft model. Together, these results suggest that Melk may provide a growth advantage for neoplastic cells and, therefore, inactivation may be therapeutically beneficial.

3T3 Cells↗

PubMed2004

Bioinformatics and cancer target discovery.

The convergence of genomic technologies and the development of drugs designed against specific molecular targets provides many opportunities for using bioinformatics to bridge the gap between biological knowledge and clinical therapy. Identifying genes that have properties similar to known targets is conceptually straightforward. Additionally, genes can be linked to cancer via recurrent genomic or genetic abnormalities. Finally, by integrating large and disparate datasets, gene-level distinctions can be made between the different biological states that the data represents. These bioinformatics approaches and their associated methodologies, which can be applied across a range of technologies, facilitate the rapid identification of new target leads for further experimental validation.

Analysis of Variance↗

PubMed2004

Signal peptide prediction based on analysis of experimentally verified cleavage sites.

A number of computational tools are available for detecting signal peptides, but their abilities to locate the signal peptide cleavage sites vary significantly and are often less than satisfactory. We characterized a set of 270 secreted recombinant human proteins by automated Edman analysis and used the verified cleavage sites to evaluate the success rate of a number of computational prediction programs. An examination of the frequency of amino acid in the N-terminal region of the data set showed a preference of proline and glutamine but a bias against tyrosine. The data set was compared to the SWISS-PROT database and revealed a high percentage of discrepancies with cleavage site annotations that were computationally generated. The best program for predicting signal sequences was found to be SignalP 2.0-NN with an accuracy of 78.1% for cleavage site recognition. The new data set can be utilized for refining prediction algorithms, and we have built an improved version of profile hidden Markov model for signal peptides based on the new data.

Amino Acid Motifs↗

PubMed2004

GEPIS--quantitative gene expression profiling in normal and cancer tissues.

MOTIVATION: Expression profiling in diverse tissues is fundamental to understanding gene function as well as therapeutic target identification. The vast collection of expressed sequence tags (ESTs) and the associated tissue source information provides an attractive opportunity for studying gene expression. RESULTS: To facilitate EST-based expression analysis, we developed GEPIS (gene expression profiling in silico), a tool that integrates EST and tissue source information to compute gene expression patterns in a large panel of normal and tumor samples. We found EST-based expression patterns to be consistent with published papers as well as our own experimental results. We also built a GEPIS Regional Atlas that depicts expression characteristics of all genes in a selected genomic region. This program can be adapted for large-scale screening for genes with desirable expression patterns, as illustrated by our large-scale mining for tissue- and tumor-specific genes. AVAILABILITY: The email server version of the GEPIS application is freely available at http://share.gene.com/share/gepis. An interactive version of GEPIS will soon be freely available at http://www.cgl.ucsf.edu/Research/genentech/gepis/. The source code, modules, data and gene lists can be downloaded at http://share.gene.com/share/gepis.

Algorithms↗

PubMed2004

Human De-etiolated-1 regulates c-Jun by assembling a CUL4A ubiquitin ligase.

Arabidopsis thaliana De-etiolated-1 (AtDET1) is a highly conserved protein, with orthologs in vertebrate and invertebrate organisms. AtDET1 negatively regulates photomorphogenesis, but its biochemical mechanism and function in other species are unknown. We report that human DET1 (hDET1) promotes ubiquitination and degradation of the proto-oncogenic transcription factor c-Jun by assembling a multisubunit ubiquitin ligase containing DNA Damage Binding Protein-1 (DDB1), cullin 4A (CUL4A), Regulator of Cullins-1 (ROC1), and constitutively photomorphogenic-1. Ablation of any subunit by RNA interference stabilized c-Jun and increased c-Jun-activated transcription. These findings characterize a c-Jun ubiquitin ligase and define a specific function for hDET1 in mammalian cells.

Amino Acid Motifs↗

PubMed2003

The secreted protein discovery initiative (SPDI), a large-scale effort to identify novel human secreted and transmembrane proteins: a bioinformatics assessment.

A large-scale effort, termed the Secreted Protein Discovery Initiative (SPDI), was undertaken to identify novel secreted and transmembrane proteins. In the first of several approaches, a biological signal sequence trap in yeast cells was utilized to identify cDNA clones encoding putative secreted proteins. A second strategy utilized various algorithms that recognize features such as the hydrophobic properties of signal sequences to identify putative proteins encoded by expressed sequence tags (ESTs) from human cDNA libraries. A third approach surveyed ESTs for protein sequence similarity to a set of known receptors and their ligands with the BLAST algorithm. Finally, both signal-sequence prediction algorithms and BLAST were used to identify single exons of potential genes from within human genomic sequence. The isolation of full-length cDNA clones for each of these candidate genes resulted in the identification of >1000 novel proteins. A total of 256 of these cDNAs are still novel, including variants and novel genes, per the most recent GenBank release version. The success of this large-scale effort was assessed by a bioinformatics analysis of the proteins through predictions of protein domains, subcellular localizations, and possible functional roles. The SPDI collection should facilitate efforts to better understand intercellular communication, may lead to new understandings of human diseases, and provides potential opportunities for the development of therapeutics.

Cell Adhesion Molecules, Neuronal↗

PubMed2003

Genome-wide identification of chromosomal regions of increased tumor expression by transcriptome analysis.

Genes up-regulated in tumor cells provide attractive anticancer therapeutic targets. Although the general underlying mechanism for the increased expression in tumors is unknown, tumor-specific up-regulation of some genes can be attributed to aberrant DNA amplification, a phenomenon common to many tumors. Using a computational method, we constructed a general transcriptome map with the human genomic sequences and expressed sequence tags in the public database. The transcriptome map revealed nonrandom chromosomal regions (termed region of increased tumor expression) where clusters of genes exhibited increased expression in the 10 tumor tissue types tested. These genomic regions often correspond to experimentally verified tumor amplicons. Our large-scale transcriptome analysis led to identification of many additional chromosomal regions with increased tumor expression, regions that represent potential tumor amplicons.

Chromosomes, Human↗

PubMed2003

Sequences in the (A)gamma-delta intergenic region are not required for stage-specific regulation of the human beta-globin gene locus.

The human beta-globin locus has been extensively studied as a model of tissue and developmental stage-specific gene expression. Structural mapping of naturally occurring mutations, including transfection and transgenic studies, and the recent finding of intergenic transcripts have suggested that there are cis-acting sequence elements in the (A)gamma-delta intergenic region involved in regulating gamma- and beta-globin gene expression. To determine whether previously identified sequences in the (A)gamma-delta intergenic region are required for appropriate developmental expression of the human beta-globin gene cluster, transgenic mice were generated by transfer of yeast artificial chromosomes containing the entire human beta-globin locus. Three different deletions of the (A)gamma-delta intergenic region were introduced, including (i) deletion of the 750-bp (A)gamma 3' regulatory element ((A)gammae), (ii) deletion of 3.2 kb upstream of the delta-globin gene encompassing pyrimidine-rich sequences and the recently described intergenic transcript initiation site, and (iii) deletion of a 12.5-kb fragment encompassing most of the (A)gamma-delta globin intergenic region. Analysis of multiple transgenic lines carrying these deletion constructs demonstrated that the normal stage-specific sequential expression of the epsilon -, gamma-, and beta-globin genes was preserved, despite deletion of these putative regulatory sequences. These studies suggest that regulatory sequences required for activation and silencing of the human beta-globin gene family during ontogeny reside proximally to the genes and immediately 5' to the human gamma- and beta-globin genes.

Animals↗

PubMed2003

A profile hidden Markov model for signal peptides generated by HMMER.

SUMMARY: Although the HMMER package is widely used to produce profile hidden Markov models (profile HMMs) for protein domains, it has been difficult to create a profile HMM for signal peptides. Here we describe an approach for building a complex model of eukaryotic signal peptides by the standard HMMER package. Signal peptide prediction with this model gives a 95.6% sensitivity and 95.7% specificity. AVAILABILITY: The profile HMM for signal peptides, data sets, and the scripts for analyzing data are available for non-commercial use at http://share.gene.com/.

Amino Acid Sequence↗

PubMed2003

Mouse endocrine gland-derived vascular endothelial growth factor: a distinct expression pattern from its human ortholog suggests different roles as a regulator of organ-specific angiogenesis.

We recently described human endocrine gland-derived vascular endothelial growth factor (EG-VEGF) as an endothelial cell mitogen with a novel selective activity and an expression pattern essentially limited to steroidogenic glands. Herein we present the identification and characterization of the mouse ortholog. The mouse cDNA and predicted amino acid sequences are, respectively, 86% and 88% identical with the human. Surprisingly, the mouse EG-VEGF transcript is predominantly expressed in liver and kidney. A comparison of human and mouse EG-VEGF promoter sequences revealed a potential binding site for NR5A1, which is known to be a pivotal element for steroidogenic-specific transcription, in the human but not mouse promoter. In situ hybridization studies localized expression of mouse EG-VEGF mRNA to hepatocytes and renal tubule cells. Interestingly, capillary endothelial cells in these sites share several common structural features with those found in steroidogenic glands. Within liver and kidney, EG-VEGF receptor expression was largely restricted to endothelial cells. Mouse EG-VEGF promoted proliferation and survival of endothelial cells. We propose that mouse EG-VEGF, like human EG-VEGF, plays a role in regulating the phenotype and growth properties of endothelial cells within distinct capillary beds.

Angiogenesis Inducing Agents↗

PubMed2002

Identification of a novel death domain-containing adaptor molecule for ectodysplasin-A receptor that is mutated in crinkled mice.

Hypohydrotic Ectodermal Dysplasia (HED) is a genetic disease seen in humans and mice. It is characterized by loss of hair, sweat glands, and teeth. The predominant X-linked form results from mutations in ectodysplasin-A (EDA), a TNF-like ligand. A phenotypically indistinguishable autosomal form of the disease results from mutations in the receptor for EDA (EDAR). EDAR is a NF-kappaB-activating, death domain-containing member of the TNF receptor family. crinkled, a distinct autosomal form of HED, was discovered in a mouse strain in which both the ligand (EDA) and receptor (EDAR) were wild-type, suggestive of a disruption further downstream in the signaling pathway. Employing a forward genetic approach, we have cloned crinkled (CR) and find it to encode a novel death domain-containing adaptor. crinkled binds EDAR through a homotypic death domain interaction and mediates engagement of the NF-kappaB pathway, possibly by recruiting TRAF2 to the receptor-signaling complex. This is an unprecedented example of naturally occurring mutations in ligand, receptor, or adaptor giving rise to the same phenotypic disease characterized by a defect in the proper development of epidermal appendages.

Adaptor Proteins, Signal Transducing↗