Biomedical subjects

Xiang H-F Zhang

Publications and source records attributed to Xiang H-F Zhang.

9 recordsLinked to original sources

PubMed2025

Tumors hijack macrophages for iron supply to promote bone metastasis and anemia.

Bone marrow is both a primary site for hematopoiesis and a fertile niche for metastasis. The mechanism of the common occurrence of anemia among patients with bone metastasis remains poorly understood. Here, we show that a specialized population of VCAM1+CD163+CCR3+ macrophages, normally essential for erythropoiesis by transporting iron to erythroblasts, are highly enriched in the bone metastatic niche in mouse models. Tumor cells hijack these macrophages for iron supply, reducing iron availability for erythroblasts, impairing erythropoiesis, and contributing to anemia. Increased iron supply enables tumor cells to produce hemoglobin in response to hypoxia, mimicking erythroblasts. We identify macrophages with similar iron-transporting features in human bone metastases and show that elevated HBB expression correlates with increased risk of bone metastasis. These findings establish iron-transporting macrophages as an essential component of the metastatic bone niche, revealing a critical interplay between immune cells, metal metabolism, and tumor cell plasticity in driving metastasis and anemia.

Animals↗

PubMed2006

Comparison of multiple vertebrate genomes reveals the birth and evolution of human exons.

Orthologous gene structures in eight vertebrate species were compared on a genomic scale to detect the birth and maturation of new internal exons during the course of evolution. We found that 40% of new human exons are alternatively spliced, and most of these are cassette exons (exons that are either included or skipped in their entirety) with low inclusion rates. This proportion decreases steadily as older and older exons are examined, even as splicing efficiency increases. Remarkably, the great majority of new cassette exons are composed of highly repeated sequences, especially Alu. Many new cassette exons are 5' untranslated exons; the proportion that code for protein increases steadily with age. New protein-coding exons evolve at a high rate, as evidenced by the initially high substitution rates (K(s) and K(a)), as well as the SNP density compared with older exons. This dynamic picture suggests that de novo recruitment rather than shuffling is the major route by which exons are added to genes, and that species-specific repeats could play a significant role in recent evolution.

Alternative Splicing↗

PubMed2006

Genome-wide RNAi screen of Ca(2+) influx identifies genes that regulate Ca(2+) release-activated Ca(2+) channel activity.

Recent studies by our group and others demonstrated a required and conserved role of Stim in store-operated Ca(2+) influx and Ca(2+) release-activated Ca(2+) (CRAC) channel activity. By using an unbiased genome-wide RNA interference screen in Drosophila S2 cells, we now identify 75 hits that strongly inhibited Ca(2+) influx upon store emptying by thapsigargin. Among these hits are 11 predicted transmembrane proteins, including Stim, and one, olf186-F, that upon RNA interference-mediated knockdown exhibited a profound reduction of thapsigargin-evoked Ca(2+) entry and CRAC current, and upon overexpression a 3-fold augmentation of CRAC current. CRAC currents were further increased to 8-fold higher than control and developed more rapidly when olf186-F was cotransfected with Stim. olf186-F is a member of a highly conserved family of four-transmembrane spanning proteins with homologs from Caenorhabditis elegans to human. The endoplasmic reticulum (ER) Ca(2+) pump sarco-/ER calcium ATPase (SERCA) and the single transmembrane-soluble N-ethylmaleimide-sensitive (NSF) attachment receptor (SNARE) protein Syntaxin5 also were required for CRAC channel activity, consistent with a signaling pathway in which Stim senses Ca(2+) depletion within the ER, translocates to the plasma membrane, and interacts with olf186-F to trigger CRAC channel activity.

Animals↗

PubMed2005

Computational searches for splicing signals.

The removal of introns from pre-mRNA requires as an initial event the accurate molecular recognition of the proper exon-intron borders. It is now evident that RNA sequence elements in addition to the consensus splice site sequences themselves are required for this recognition. Genomic analyses have contributed to the definition of these elements as exonic and intronic splicing enhancers and silencers, comprising what has been called the "splicing code." Many computational methods have been brought to bear in such studies. We describe here some of the methods we have used to discover functional splicing signals. What these methods have in common is a comparison of sequences in and around exons to sequences found elsewhere in the genome. We have especially made use of comparisons to "pseudo exons," intronic sequences resembling exons by virtue of being bounded by sequences indistinguishable from splice sites. Two computational strategies are emphasized: (1) the use of a machine learning technique in which a computational algorithm, a support vector machine, is first trained on known examples and then used to predict sequences associated with splicing; and (2) straight statistical analysis of differences between regions associated with exons and other regions in the genome. In most cases, the predictions made using these methods have been validated by subsequent empirical tests. An attempt has been made to make this description understandable by researchers unfamiliar with computational practice and to include practical references to specific databases and programs.

Alternative Splicing↗

PubMed2005

Dichotomous splicing signals in exon flanks.

Intronic elements flanking the splice-site consensus sequences are thought to play a role in pre-mRNA splicing. However, the generality of this role, the catalog of effective sequences, and the mechanisms involved are still lacking. Using molecular genetic tests, we first showed that the approximately 50-nt intronic flanking sequences of exons beyond the splice-site consensus are generally important for splicing. We then went on to characterize exon flank sequences on a genomic scale. The G+C content of flanks displayed a bimodal distribution reflecting an exaggeration of this base composition in flanks relative to the gene as a whole. We divided all exons into two classes according to their flank G+C content and used computational and statistical methods to define pentamers of high relative abundance and phylogenetic conservation in exon flanks. Upstream pentamers were often common to the two classes, whereas downstream pentamers were totally different. Upstream and downstream pentamers were often identical around low G+C exons, and in contrast, were often complementary around high G+C exons. In agreement with this complementarity, predicted base pairing was more frequent between the flanks of high G+C exons. Pseudo exons did not exhibit this behavior, but rather tended to form base pairs between flanks and exon bodies. We conclude that most exons require signals in their immediate flanks for efficient splicing. G+C content is a sequence feature correlated with many genetic and genomic attributes. We speculate that there may be different mechanisms for splice site recognition depending on G+C content.

Animals↗

PubMed2005

Exon inclusion is dependent on predictable exonic splicing enhancers.

We have previously formulated a list of approximately 2,000 RNA octamers as putative exonic splicing enhancers (PESEs) based on a statistical comparison of human exonic and nonexonic sequences (X. H. Zhang and L. A. Chasin, Genes Dev. 18:1241-1250, 2004). When inserted into a poorly spliced test exon, all eight tested octamers stimulated splicing, a result consistent with their identification as exonic splicing enhancers (ESEs). Here we present a much more stringent test of the validity of this list of PESEs. Twenty-two naturally occurring examples of nonoverlapping PESEs or PESE clusters were identified in six mammalian exons; five of the six exons tested are constitutively spliced. Each of the 22 individual PESEs or PESE clusters was disrupted by site-directed mutagenesis, usually by a single-base substitution. Eighteen of the 22 disruptions (82%) resulted in decreased splicing efficiency. In contrast, 24 control mutations had little or no effect on splicing. This high rate of success suggests that most PESEs function as ESEs in their natural context. Like most exons, these exons contain several PESEs. Since knocking out any one of several could produce a severalfold decrease in splicing efficiency, we conclude that there is little redundancy among ESEs in an exon and that they must work in concert to optimize splicing.

Alternative Splicing↗

PubMed2004

Computational definition of sequence motifs governing constitutive exon splicing.

We have searched for sequence motifs that contribute to the recognition of human pre-mRNA splice sites by comparing the frequency of 8-mers in internal noncoding exons versus unspliced pseudo exons and 5' untranslated regions (5' untranslated regions [UTRs]) of transcripts of intronless genes. This type of comparison avoids the isolation of sequences that are distinguished by their protein-coding information. We classified sequence families comprising 2069 putative exonic enhancers and 974 putative exonic silencers. Representatives of each class functioned as enhancers or silencers when inserted into a test exon and assayed in transfected mammalian cells. As a class, the enhancer sequencers were more prevalent and the silencer elements less prevalent in all exons compared with introns. A survey of 58 reported exonic splicing mutations showed good agreement between the splicing phenotype and the effect of the mutation on the motifs defined here. The large number of effective sequences implied by these results suggests that sequences that influence splicing may be very abundant in pre-mRNA.

5' Untranslated Regions↗

PubMed2004

Latent splice sites and stop codons revisited.

The accuracy of the data we reported in an RNA Letter to the Editor earlier this year on the possible relationship between stop codons and splicing is questioned by Miriami et al. (this issue). We reply here that we see no inaccuracy in our data presentation and offer a possible explanation for their interpretation.

Codon, Terminator↗

PubMed2003

Sequence information for the splicing of human pre-mRNA identified by support vector machine classification.

Vertebrate pre-mRNA transcripts contain many sequences that resemble splice sites on the basis of agreement to the consensus,yet these more numerous false splice sites are usually completely ignored by the cellular splicing machinery. Even at the level of exon definition,pseudo exons defined by such false splices sites outnumber real exons by an order of magnitude. We used a support vector machine to discover sequence information that could be used to distinguish real exons from pseudo exons. This machine learning tool led to the definition of potential branch points,an extended polypyrimidine tract,and C-rich and TG-rich motifs in a region limited to 50 nt upstream of constitutively spliced exons. C-rich sequences were also found in a region extending to 80 nt downstream of exons,along with G-triplet motifs. In addition,it was shown that combinations of three bases within the splice donor consensus sequence were more effective than consensus values in distinguishing real from pseudo splice sites; two-way base combinations were optimal for distinguishing 3' splice sites. These data also suggest that interactions between two or more of these elements may contribute to exon recognition,and provide candidate sequences for assessment as intronic splicing enhancers.

Artificial Intelligence↗