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Evolution of gene expression patterns in a model of branching morphogenesis

Anna Pavlova, Robert O. Stuart, Martin Pohl, and Sanjay K. Nigam

Renal Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

Branching morphogenesis of the ureteric bud in response to unknown signals from the metanephric mesenchyme gives rise to the urinary collecting system and, via inductive signals from the ureteric bud, to recruitment of nephrons from undifferentiated mesenchyme. An established cell culture model for this process employs cells of ureteric bud origin (UB) cultured in extracellular matrix and stimulated with conditioned media (BSN-CM) from a metanephric mesenchymal cell line (H. Sakurai, E. J. Barros, T. Tsukamoto, J. Barasch, and S. K. Nigam. Proc. Natl. Acad. Sci. USA 94: 6279-6284, 1997.). In the presence of BSN-CM, the UB cells form branching tubular structures reminiscent of the branching ureteric bud. The pattern of gene regulation in this model of branching morphogenesis of the kidney collecting system was investigated using high-density cDNA arrays. Software and analytical methods were developed for the quantification and clustering of genes. With the use of a computational method termed "vector analysis," genes were clustered according to the direction and magnitude of differential expression in n-dimensional log-space. Changes in gene expression in response to the BSN-CM consisted primarily of differential expression of transcription factors with previously described roles in morphogenesis, downregulation of pro-apoptotic genes accompanied by upregulation of anti-apoptotic genes, and upregulation of a small group of secreted products including growth factors, cytokines, and extracellular proteinases. Changes in expression are discussed in the context of a general model for epithelial branching morphogenesis. In addition, the cDNA arrays were used to survey expression of epithelial markers and secreted factors in UB and BSN cells, confirming the largely epithelial character of the former and largely mesenchymal character of the later. Specific morphologies (cellular processes, branching multicellular cords, etc.) were shown to correlate with the expression of different, but overlapping, genomic subsets, suggesting differences in morphogenetic mechanisms at these various steps in the evolution of branching tubules.

cluster analysis; vector analysis; kidney development; ureteric bud; tubulogenesis


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

A FUNDAMENTAL MECHANISM by which a variety of epithelial tissues (e.g., kidney, breast, prostate, salivary gland. and lung) develop is branching morphogenesis (2, 7, 26, 30, 44, 68, 80, 81, 84, 89). In different in vitro model systems and in genetically engineered mice, a variety of molecules, including growth factors, extracellular matrix proteins, integrins, proteases, and protease inhibitors have been implicated as effectors of branching morphogenesis. However, these studies have usually focused on a single molecule based on an intuitive approach, whereas it is increasingly apparent that such a complex process as repetitive branching morphogenesis will involve the coordinate expression of many genes. These genes may well be different than those that are currently being studied. Thus a broad approach to identifying these genes and analyzing their temporal expression patterns is crucial to defining potential interactions between genes that may play essential roles in branching morphogenesis.

An ideal system to accomplish this analysis is a recently described cell culture model that employs cells derived from the ureteric bud (UB) seeded in an extracellular matrix gel (73). In this system, cells of UB origin (Dolichos biflorus binding, epithelial marker expression) derived from an SV40 large-T transgenic mouse are observed to undergo profound morphological changes in response to the conditioned media from another cell line of metanephric mesenchymal origin (BSN cells) likewise derived from an SV40 transgenic mouse. This system provides an extremely simple model for events in kidney development, in which it is thought that morphogenetic signals from the metanephric mesenchyme induce branching and growth of the ureteric bud; in fact, it has recently been shown that BSN cell conditioned media (BSN-CM) induces branching morphogenesis of the isolated UB in the absence of contact with mesenchyme under conditions similar to the cell culture model (60a). In the cell culture model, morphological changes in the suspended UB cells proceed through defined stages including the extension of cellular processes, formation of multicellular cords, and eventually multicellular branching tubular structures. The final tubular structures bear a resemblance to branching ureteric bud in the developing kidney (Fig. 1).


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Fig. 1.   Confocal images of ethidium bromide-stained UB cells in three-dimensional collagen matrix culture. a: 24 h, DMEM-F12 with BSN-CM demonstrating early process formation. b and e: Confocal and phase-contrast images at 72 h of culture in BSN-CM demonstrating multicellular cords. d: Confocal section of multicellular cyst resulting from culture in Matrigel without BSN-CM. c and f: Confocal and phase-contrast images at 1 wk of culture in BSN-CM and collagen matrix demonstrating extensive branching tubulogenesis. Bar = 10 µm.

Many methods exist for the determination of gene expression. Northern blotting, RNase protection, and quantitative RT-PCR depend on prior knowledge of sequence and may be used to quantify a relatively few RNA species. We have previously employed these focused methods for the quantification of likely morphogenetic effectors in the three-dimensional matrix system (73-76). Other methods such as differential display PCR (ddPCR), its variants such as codon-optimized ddPCR (coddPCR), and subtractive hybridization offer the ability to identify novel differentially expressed sequences; however, these suffer in terms of being labor-intensive and in the need to independently validate findings (18, 33, 43, 46-49, 54, 56, 79, 99, 100). Several newer methods including serial analysis of gene expression (SAGE) and arrays of cDNAs, either on membranes, glass slides, or microchips, allow quantification of the expression of a large number of known sequences (12, 23, 53, 63, 82, 94). Recently, nylon membrane arrays of known mouse genes have become available, which for the first time allow for the parallel screening of a large number of genes for differentially expressed sequences.

Broad analysis of gene expression by cDNA array analysis allows for identification of previously unsuspected individual changes in transcription. The highly parallel nature of the analysis offers the opportunity to integrate many individual changes in gene expression into a theoretical framework. In this report, we describe the application of high-density cDNA array analysis to a model for ureteric bud branching morphogenesis. In addition, we describe a method of analysis including software for the quantification of cDNA array autoradiograms. The approach should be generally applicable to larger cDNA arrays of any type as these become available.


    METHODS
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

Tissue culture. Plastic ware and tissue culture supplies were from Falcon and Life Technologies, respectively. Both the UB and BSN cell lines were derived from microdissected embryonic day 11.5 SV40 transgenic mouse embryos as previously described (4, 73). Monolayer and three-dimensional collagen matrix culture of UB cells and production of BSN-CM were performed as described previously (5, 10, 73, 75-78). Briefly, BSN cells were maintained in DMEM-F12 10% serum at 37°C in 5% CO2 atmosphere. For production of BSN-conditioned media (BSN-CM), the cells were rinsed three times in DMEM-F12 containing no serum and then incubated in DMEM-F12 without serum for 4 days. The conditioned media was cleared of any particulate matter by centrifugation followed by filtration through 0.22-µm syringe filters (Millipore) and stored at 4°C until use. The UB cells were maintained at 32°C in DMEM-F12 containing 10% FCS. The cells were incubated in PBS and lightly trypsinized prior to either confluent monolayer culture or suspension in three-dimensional 1% collagen matrix in ~10-cm tissue culture dishes. Either DMEM-F12 or the same media conditioned by the BSN cells was applied to the cells and changed every other day. Progress of morphogenetic events was monitored by phase contrast microscopy and recorded by standard photographic technique.

cDNA arrays. cDNA arrays on nylon membranes containing 588 unique known murine genes in duplicate were obtained from Clontech Laboratories. The membranes were probed with 32P-labeled cDNA synthesized from mRNA by a modification of the manufacturer's directions. Briefly, total RNA was isolated from cells in either the monolayer or in collagen matrix using Tri-Reagent-LS (Molecular Research Center). The three-dimensional collagen matrices containing cells were rapidly dehydrated on 3MM Whatmann filters before solubilization. Poly-A RNA was then isolated from total RNA using Oligotex Midi kits (Qiagen), and 500 ng mRNA was used for synthesis of the 32P-labeled cDNA probe using a master mix of gene-specific primers for reverse transcription provided by the manufacturer. Labeled cDNA probe was then separated from unincorporated [32P]dATP on Chroma Spin-200 columns (Clontech). After quantification, 1 × 106 cpm/ml probe in ExpressHyb solution (Clontech Laboratories) was applied to prehybridized Atlas Arrays. Arrays were hybridized overnight at 68°C and extensively washed in 2× SSC followed by 0.1× SSC with 0.1% SDS at 68°C and exposed to Biomax (Kodak) autoradiographic film for up to 1 wk (Fig. 2).


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Fig. 2.   cDNA array quantification. A: representative cDNA array autoradiogram. B: VectorArray software user interface. Cells are automatically classified as: expressed (green), background (red), unsuitable for use as background (black), or containing unretrievable data (white). Cell assignment may be changed by clicking with the computer's mouse. Integrated pixel densities (IPD) of each expressed cell corrected for nearest background cell values are exported in a format compatible with spreadsheet programs.

Analytical methods and software. Even the moderate number of data points represented by 588 genes across several experimental conditions offered considerable challenge in data analysis and interpretation, which quickly overwhelmed the utility of direct visual comparison of the grids. To quantify the arrays and analyze the resulting data, we developed VectorArray, an application written in Microsoft Visual Basic 5.0 for Windows NT/98/95. The VectorArray program includes a module for the quantification of signal intensities from bitmap images of either autoradiographic or phosphorimager data. The image processing algorithm includes overlaying a "grid" on the autoradiogram to define cells, after which definition of individual cell boundaries and quantification are then accomplished by standard perimeter-finding and pixel summation techniques. The program automatically categorizes "cells" in the grid image as expressed, background, or dirty, on the basis of the distribution of signal within each cell, and then presents a point and click interface for user defined cell-assignment changes (Fig. 2). In this way, the laborious task of checking a long list of numbers for agreement with the raw data may be avoided: classification is accomplished at the outset. Regionalized background subtraction is employed in which the integrated pixel densities (IPD) of a user-specified minimum number of nearest neighboring background cells are averaged and subtracted from the IPD of each cell under analysis. Output is suitable for import into spreadsheet programs and consists of the IPD and area in pixels for each autoradiographic signal. The VectorArray program is available via the internet (http://medicine.ucsd.edu/rostuart/).

Raw data representing signal intensities may be represented in two- and greater-dimensional scatter plots. Systat 7.0 (SPSS Inc.) was used for visualization of two and three-dimensional scatterplots of the raw and log-transformed IPD data. Each data point occupied the coordinates specified by background-corrected signal intensity in n dimensions (experimental conditions). It was uniformly the case that, with reasonably similar autoradiographic exposures, two-dimensional scatter plots of the signal intensities revealed a strong central tendency corresponding to genes with identical expression, despite in some cases quite different raw signal intensities (Fig. 3). Thus the transcriptional states corresponding to the various experimental conditions were quite similar in that the vast majority of genes assayed had no apparent change in expression. Those data points found to either side of the best-fit line were thus considered to be differentially expressed with the distance to the line-of-identity a function of the degree of differential expression. To formalize this notion, a computational module in VectorArray was used to calculate vectors in two-dimensional space (either orthogonal or in the dimension of the control condition) from each data point to the best-fit line of identical expression. In the case of three or more (n) dimensions (experimental conditions compared simultaneously), each gene generates n component vectors, one for each two-dimensional projection plane. The magnitude of each vector provides a simple measure of differential expression, while its sign indicates increased vs. decreased relative expression (Fig. 4). Points representing the expression of individual genes under several conditions segregate into distinct groups when their component vectors are plotted (Fig. 5), providing the basis for cluster analysis based on both the direction and magnitude of change in gene expression.


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Fig. 3.   Linearity of pair-wise comparison. A: signal intensity as a function of exposure in the same cDNA array hybridization experiment. Data displayed as IPD for light and dark exposures (exp.). Note that differing exposure may produce markedly different absolute values of signal despite no change in levels of expression. Scatterplot readily defines the relationship between the two exposures. B: signal intensity as a function of exposure for light and very dark exposure (v. dark exp.). Note signal saturation resulting in marked deviation from linear relationship.



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Fig. 4.   Pair-wise comparison: UB cells treated (y-axis) vs. not treated (x-axis) with BSN-CM. Data expressed as log(IPD) with linear regression line. Monolayer (ml) UB cells were either treated with BSN-CM (b+) or not (b-) in media supplemented with 10% FCS (s-10%). Distance from line (dy) is a measure of differential gene expression.



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Fig. 5.   Multi-dimensional analysis of cDNA array data. Multiple conditions may be analyzed simultaneously via cDNA arrays. UB cell gene expression was determined at the beginning of tubulogenesis experiments (monolayer, no BSN-CM) and at 1 day (gel, 24 h) and 7 days (gel, 1 wk) of collagen-matrix culture with BSN-CM. A: signal intensities (IPD) displayed as a three-dimensional scatter plot. B: vector analysis of the log-transformed data. Where data in the x-axis (A) was taken as the control condition, the scalar components of vectors in the y- and z-axes were plotted yielding clusters x, y, z, and the intermediate clusters xz, xy, and yz. The cluster representing "housekeeping" genes with less than 0.3 log (twofold) change lie in the center of the graph and have been omitted.

In the case of pair-wise comparisons of gene expression, a concise ordered list of relative changes in gene expression is generated based on the distance from a line of identical expression (Fig. 4; Tables 1 and 2). Vector analysis of more complex systems generates simplified patterns with easily recognized clusters. The example provided demonstrates the reduction of a three-dimensional data matrix without obvious clustering to a mathematically derived "Venn diagram" (Fig. 5). In addition, since these operations are carried out on a log-scale, many orders of magnitude of signal intensity may be grouped together and compared. The clusters obtained by this method have both meaningful biological interpretations and correlate well with perceived signal intensities observed in the original autoradiograms (Fig. 6). Experiments were done in duplicate, and changes in expression were deemed significant if they were concordant. A log distance of 0.2 corresponds to a roughly 50% increase in signal intensity, while the sign, positive or negative, denotes upregulation vs. downregulation.

                              
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Table 1.   Changes in gene expression induced by BSN-CM



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Fig. 6.   Cluster definitions. Expression profiles of all members of the clusters identified by vector analysis are shown at left. Representative original autoradiographic spots are shown at right, along with descriptions. Clusters are generically labeled x, y, z, xy, xz, and yz according to preferential axis of expression in the original three-dimensional scatterplot.

Functional annotation, in addition to that provided by the manufacturer, for the sequences present in the arrays was accomplished by sequence similarity comparisons to public sequence databases with extensive functional information. The Clusters of Orthologous Groups (COG) database (ftp://ncbi.nlm.nih.gov) contains precise functional definitions for >6,000 sequences from 6 organisms including yeast (90). Wormpep (http://www.sanger.ac.uk/Projects/C_elegans/wormpep/index.shtml), likewise, contains extensive functional information on many of ~19,000 sequences from Caenorhabditis elegans (8, 13, 71). To link the array genes to the functional annotations in the larger databases, software tools were developed to extract peptide sequences from each related GenBank or SwissProt entry and then format the information as a functionally annotated FASTA format file suitable for use as a database in "stand-alone" BLAST searching using the murine sequences as queries (1).


    RESULTS
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

The analytical methods employed in the present work were designed to deal with several pitfalls in the quantification of cDNA array autoradiographic data: the intra- and inter-array wide range of signal intensity in both the autoradiographic spots and the background, validity of spot selection, and differences in exposure. As described in METHODS, the algorithm employed allows the user to select valid background and expressed "cells" by pointing and clicking using the computer's mouse. In this way, signal intensities representing questionable or spurious signals (extraneous spots, overlapping signals) are flagged as such at the outset of analysis. In addition, as no two autoradiographic experiments can ever have precisely the same "exposure," apparent differences in signal intensity will appear that do not represent true changes in gene expression. To investigate the ability of the system to provide meaningful results in the setting of a broad range of input, we exposed membranes to autoradiographic film over a considerable range of time, up to 1 wk in some cases. We found that, within a certain range, when the IPDs of each expressed cell in different exposures of the same membrane were displayed on scatterplots, an impressive linear relationship existed (Fig. 3A). Note that the absolute values of IPD are roughly twice the value on the x-axis (lighter exposure) than on the y-axis (darker exposure). Nevertheless, as the exposures represent the same experiment, no true difference in expression is indicated. Rather, all data points fall roughly on a straight line, which in this case is known to represent equivalent expression. Marked overexposure of a grid results in saturation of a number of cells and results in easily recognizable nonlinearity (Fig. 3B). As it is not our goal to compare the signal intensity representing one gene vs. another on the same grid, the wide range of signal intensities provide an internal control for exposure within the usable linear range of signal intensity. In subsequent experiments, exposures within this linear range of response were used for analysis.

Although scatterplots of IPD rapidly identify important changes in gene expression and at the same time account for changes in exposure, most data clusters at lower values of IPD and is not easily visualized together with highly expressed genes. To represent the range of densitometric values present in a single array and between arrays, the data were transformed by log(IPD+1), hereafter referred to as log(IPD). The vector of each data point to the regression line was then calculated (Fig. 4). As indicated in methods, the magnitude of the vector in log-space then serves as a convenient measure of the magnitude of differential gene expression in the experimental conditions under analysis, while the direction of the vector indicates up- or downregulation under experimental conditions.

Vector analysis may be used to identify changes in the transcriptional state of the UB cells that must accompany the marked changes in morphology induced by the BSN-CM. Many of these changes in gene expression presumably reflect patterns necessary for branching morphogenesis to occur. Such changes may include differential expression of a variety of molecules including proteinases and their inhibitors, extracellular matrix molecules and their receptors, cytoskeletal proteins, cell-adhesion molecules, and as yet unsuspected morphogenetic effectors and targets. However, it is also quite possible that some fraction of the apparent morphogenetic activity of the BSN-CM is the result of autocrine secretion from the UB cells themselves. In this case, BSN-CM might be expected to upregulate the transcription of secreted factors in the UB cells that might be identifiable as changes on cDNA arrays. To elucidate the effect on UB cell transcription of the BSN-CM, we exposed UB cells to BSN-CM under a variety of conditions (Figs. 1, 4, and 5). Transcriptional activity in the 588 genes was then quantified using the cDNA arrays and the VectorArray program described in methods. The effect of BSN-CM was investigated in monolayer as well as collagen matrix culture. In addition, gene expression was profiled on a background of varying concentrations of serum supplementation.

A typical scatterplot for a pair-wise comparison demonstrating up- and downregulated sequences is shown in Fig. 4. Data points removed from the trend-line (by distance, dy) are considered to be differentially expressed with respect to the control condition. In this model for branching morphogenesis, a select few classes of genes were found to be consistently up- or downregulated in the UB cells under very different conditions (Table 1). By and large, changes segregate into logical groups: 1) differential expression of transcription factors with previously described roles in morphogenesis, 2) downregulation of pro-apoptotic genes accompanied by upregulation of anti-apoptotic genes, and 3) upregulation of a small group of secreted products. As mentioned previously, the induction of UB-secreted factors by BSN-CM raises the intriguing possibility of autocrine signaling in this model system. One consistently upregulated transcript in our studies was neuroleukin, also known as autocrine motility factor (AMF) and glucose-6-phosphate isomerase (GPI). In its secreted form, AMF functions as a neuronal growth factor and as an inducer of cell motility in fibroblastic cell lines (83, 98) in a manner reminiscent of hepatocyte growth factor (HGF). Northern analysis of AMF and other differentially regulated genes confirmed the array findings and demonstrated that even on a background of 10% serum supplementation, BSN-CM upregulated the expression of AMF (Fig. 7).


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Fig. 7.   Northern analysis. Transforming growth factor-beta (TGF-beta ), autocrine motility factor (AMF), and tissue inhibitor of metalloproteinases 3 (TIMP-3) were identified in the cDNA arrays as upregulated in UB cells by BSN-CM. In separate experiments, and under a variety of culture conditions, these findings are confirmed by Northern analysis.

The effects of known morphogenetic factors account for perhaps only 50% of the branching morphogenetic and tubulogenic activity present in BSN-CM (76). This growth factor-rich medium then likely contains uncharacterized morphogenetic substances. An alternative method to biochemical purification of morphogenetic substances from the BSN-CM is a complete inventory of secreted factors expressed by the BSN cells. Unfortunately, a complete repertoire of secreted factor genes is not yet available, nor present on commercial cDNA arrays. We nevertheless surveyed gene expression in the BSN cells and compared the pattern of expression to that of UB cells. Likely morphogens in this system would, by definition, be differentially expressed in the BSN cells relative to the UB cells. In addition, in cases where cognate receptors are known (and present in the arrays), their expression in the UB cells can be determined. Genes were characterized as secreted vs. not secreted on the basis of sequence similarity to genes in functionally annotated public databases as outlined in methods. Several secreted factors represented in the cDNA arrays were found to be expressed in the BSN cells but not in the UB cells (Table 2). Among these are bone morphogenetic proteins (BMP) 1 and 4, as well as insulin-like growth factor I (IGF-I), each of which have been previously identified as candidate morphogens during development (3, 19, 20, 28, 29, 31, 35, 37, 50-52, 55, 60, 65, 69, 70, 88, 91). Similar analysis of arrays containing a larger complement of genes and ESTs might be expected to identify novel, or unsuspected, morphogens.

                              
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Table 2.   Secreted factors expressed by UB and BSN cells

The state of differentiation of the two cell lines may be investigated by extending the analysis to include nonsecreted proteins (Table 3). Although, to our knowledge, no gene present on the arrays is perfectly specific for epithelial vs. mesenchymal tissue, observed differences in gene expression between the cell lines support the largely epithelial character of the UB cells (Table 3). Fewer genes were found to be expressed uniquely in the BSN cell line. However, these results also support prior results suggesting that BSN cells are less differentiated or perhaps mesenchymal in character (73). Note that both cell lines express vimentin, not an uncommon finding in SV40 T-antigen-transformed cells. Interestingly, there was a clear distinction in the expression of cytokeratins: the "prototypical" simple epithelial molecule, cytokeratin-18, was expressed uniquely in the UB cells, whereas cytokeratin-19 was found uniquely in the BSN cells.

                              
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Table 3.   State of differentiation of UB and BSN cells

Analysis of gene expression is not limited to pair-wise comparisons; similar calculations may be carried out in an arbitrary number of dimensions/conditions. We therefore sought a concise description of changes in gene expression with respect to time in the UB/BSN cell model system by comparing expression profiles in UB cells in monolayer culture without BSN-CM and those of UB cells in three-dimensional matrix culture at 24 h and 1 wk in the presence of BSN-CM. cDNA arrays were hybridized with probes derived from these conditions, and the autoradiograms were quantified using the VectorArray program. The data may be expressed as a three-dimensional data matrix with magnitude along each axis corresponding to expression (in IPD) in each experimental condition (Fig. 5A). As was the case for pair-wise comparisons, the magnitude and direction of a vector from each data point to a best-fit line representing equivalent expression may be calculated. The scalar components of each vector may then be plotted (Fig. 5B).

The graphical representation of the vector analysis groups genes into meaningful clusters based on their transcriptional behavior in this system despite a three-log variation in baseline expression. Data points cluster at the points of the plot according to preferential expression in one of the three conditions tested, or in intermediate zones representing expression in two conditions. Genes with little change in expression (nearest the line of identity in Fig. 5A) are grouped near the center of the plot. Genes with less than 0.4 log unit distance (roughly 2.5-fold change) from the line of equivalent expression have been omitted. The distance of data from the center of the plot correlates with relative change in expression. Data may be further coded for intensity of expression. It may be seen that autoradiographic spots quantified over 4 orders of magnitude (IPD) may be grouped together in this manner (Fig. 5B).

Vector analysis of the present data immediately categorizes genes represented on the cDNA arrays (Fig. 6). The data-defined clusters (generically termed x, y, and z) have meaningful biological interpretations. Thus genes in group x are seen to be downregulated by exposure to the three-dimensional matrix environment, those in group y are transiently upregulated in this system, and those in group z are transcriptionally active only after long-term culture. Within each directionally defined cluster, two subclusters are identifiable based on the threshold of signal detection in this system. Among genes transiently upregulated (group y) were heat-shock and related genes: osmotic stress protein (Osp94), growth arrest and DNA damage inducible protein (Gadd45), as well as pro-apoptotic genes such as caspase-11.

It is difficult in this model system to completely separate the roles of those genes involved in tubulogenesis per se from those functions associated primarily with proliferation. Nevertheless, a number of genes were found persistently upregulated in conditions favoring branching morphogenesis (collagen matrix with BSN-CM, group yz) including Pax-8, membrane-type metalloproteinase, c-met, basic fibroblast growth factor (bFGF) receptor, ephrin-A5, ephrin-B2, tissue plasminogen activator, CD44, and three homeobox genes, Hox-B5, -B8, and -B9. The role of these genes in branching morphogenesis clearly deserves further investigation. Representative member genes from each group are in Table 4.

                              
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Table 4.   Representative members of gene clusters


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

Parallel analysis of the transcriptional activity of a large number of genes holds great promise in elucidating developmental mechanisms. Nevertheless, analysis of whole organ samples or even isolated tissues in culture is complicated by the presence of diverse cell types. On the other hand, analysis of a single cell type in a well-defined model system affords the opportunity to ascribe changes in gene expression to a given cell and perhaps better correlate changes in transcription with morphological events. Here we describe the application of "high-density cDNA array analysis" to a well-defined model system for the development of the collecting system of the kidney. In addition, we describe a generally applicable approach to the analysis of high-density cDNA arrays. Interactive software has been developed that effectively quantifies autoradiographic data obtained from cDNA arrays. In addition, a simple analytical approach is presented that circumvents many potential pitfalls in, and allows quick and intuitive interpretation of, such data. The analytical method, in the context of the three-dimensional branching morphogenesis culture system, allows the clustering of potential morphogenetic genes into functionally relevant units. The clustering algorithm based on the vector analysis of directional changes in signal intensities would be expected to be generally applicable to data derived from high-density cDNA arrays on "chips," glass slides, as well as the nylon arrays used in the present studies.

In the UB cell/BSN-CM model system, conditioned media from the BSN cell induces marked morphological changes in the UB cells reminiscent of the behavior of ureteric bud during renal development (Fig. 1), and this same conditioned media is an essential component in a model for isolated UB culture and branching (66a). It was hypothesized that changes in gene expression seen in this model system have relevance to the in vivo situation. As an initial step toward identification of morphogenetic effectors from the pool of previously characterized genes, high-density cDNA array analysis of gene expression was employed. In addition, we sought a more extensive characterization of the two cell lines employed in these studies.

The pattern of gene expression in the UB cells is typical of simple, nonstratified, epithelium. Our findings that the UB cells expressed ZO-1, casein kinase II, and cytokeratin-18, taken together with the previous demonstration that the cells stain with E-cadherin and D. biflorus (lectin which binds specifically to ureteric bud), leave little doubt as to their origin (73). Several other genes were found specifically in the UB cells that are more or less restricted to epithelial cells, depending on the context (Table 3).

The pattern of gene expression in the BSN cells differs markedly from that of the UB cells. Although many genes were found uniquely in the UB cells, very few were unique to the BSN cells. This is consistent with the notion that the UB epithelial cell phenotype is more differentiated than the BSN cells, which are less differentiated and mesenchymal in nature, and supports the speculation that the program for the epithelial phenotype represents an "overlay" on the less differentiated ground state. Of the few genes found uniquely in BSN cells (in the context of the two-cell system employed), both IGF-I and R-ras have relatively mesenchymal distributions of expression in some systems (42, 67). Notably, in developing lung, another organ that is formed through epithelial-mesenchymal interactions and branching morphogenesis, IGF-I expression is confined to the mesenchyme (67).

The expression of cytokeratins is typically associated with identity as epithelium, whereas expression of vimentin is taken to connote a mesenchymal character. Care must be taken to avoid facile interpretations in the context of transformed cell lines, as SV40 T-antigen-transformed cells often express vimentin regardless of other aspects of phenotype (36). In addition, coexpression of vimentin and cytokeratins is well described in immature renal tubule cells (93). Both the UB cells and BSN cells coexpress vimentin and cytokeratin molecules; however, with differing patterns. Coexpression of cytokeratin-18 and vimentin in the UB cells is expected and consistent with the presence of T-antigen in a simple epithelial cell type. The coexpression of vimentin with cytokeratin-19 in the mesenchymally derived BSN cells is open to wider interpretation. It is conceivable that these cells are partially differentiated toward the epithelial cell type. In this context, it is interesting to note that cytokeratin-19 is, in other settings, associated with a variable or "labile" state of differentiation (85). In any case, the present findings provide only an initial hint of the overall situation regarding the states of differentiation of these cells given that the 588 genes present on the arrays represent at best ~1% of potentially expressed genes in the mouse. A definitive answer (and perhaps a true definition of epithelial vs. mesenchymal tissue) will, perhaps, be provided upon availability of very-high-density arrays covering most or all of the genome.

The expression profiles of the BSN and UB cells also differed with respect to secreted factors. It might be expected that a soluble peptide factor secreted by the BSN cells with morphogenetic activity in the UB cells would be expressed in the BSN cells and not in the UB cells. Any secreted factor detectable in both cell lines would be a less likely candidate morphogen, as it could act as an autocrine factor, and, in this model, UB cells do not form tubules without some factor present in BSN-CM. The few secreted protein RNA species found exclusively in the BSN cells all represent candidate morphogens in this system (Table 2). Both IGF-I and BMP-4 have well-described and suspected roles in kidney and collecting system development (31, 37, 51, 61, 91, 96). The IGF binding proteins (IGFBP) are likewise known to modulate the activity of IGF and have been demonstrated in the developing kidney in spatial and temporal patterns of expression suggestive of a role in mesenchymal-to-epithelial transition (57). Both cathepsin-B and BMP-1 may have morphogenetic effects by altering the balance of proteolytic or growth factor activity in the experimental milieu (88). In fact, IGF-I and the IGFBP proteins are known substrates of cathepsin D (15, 16). A complex cross talk between the ureteric bud and mesenchyme involving, IGF-I, IGFBPs, and cathepsins could be postulated, given the pattern of expression of these molecules (Table 2).

Downstream from the production of BSN cell-derived soluble morphogens are effector molecules manufactured by the UB cells. On the basis of what is known about collecting system development from in vitro studies and genetically engineered mice, changes in the transcription of a number of likely morphogenetic effectors might be predicted a priori, including transcription factors, cell adhesion molecules, extracellular matrix proteins and their integrin receptors, extracellular proteinases and their inhibitors, and perhaps autocrine/paracrine secreted factors and their receptors (60a, 86, 87). The effect of BSN-CM on the state of transcription of the UB cells was investigated in both monolayer and collagen culture, in the absence of and with variable amounts of supplemental serum, and for periods of time of up to 1 wk in collagen culture. The changes in gene expression in the UB cells consistently induced by BSN-CM paralleled general predictions with respect to transcription factors and extracellular proteinases (Tables 1 and 4). Perhaps less readily predictable were the transient changes noted in heat-shock/stress proteins after suspension in collagen and the reciprocal changes in the expression of pro- and anti-apoptotic genes (Table 1).

Among the stress proteins observed to be upregulated either transiently (Table 4, Fig. 5B; group y) or persistently (Table 4, Fig. 5B; group yz) in UB cells after suspension in collagen were osmotic stress protein-94 (Osp94, despite predicted osmolality of the culture milieu to be nearly isosmotic), HSP-86, and an oxidative stress-induced protein. Coincidentally, several pro-apoptotic genes were transiently increased including caspase-11, etoposide-induced p53 responsive RNA, and Gadd45. BSN-CM appeared to induce transcription of defender against cell death 1 (DAD-1) and FLIP-1 apoptosis inhibitor. It appears, then, that transfer of UB cells from monolayer culture into a three-dimensional collagen culture environment induces a stress response, perhaps even "matrix shock." Furthermore, it is likely that BSN-CM contains survival factors that induce anti-apoptotic genes.

Our data suggest that the expression of a number of transcription factors are regulated by soluble factors that mediate branching morphogenesis. These included the following: Pax-8, CACCC box-binding protein BKLF, DP-1 cell cycle regulatory transcription factor, NF-1B, and homeobox proteins B5, B8, and B9. The differential expression of homeobox and related genes is particularly intriguing given their role in patterning and segmentation at other times in development. There are at least two kinds of patterning decisions that might be regulated by the broad class of homeobox genes: the pattern of arborization and the structural and functional segmentation of the developing nephron. As discussed above, the branching pattern is likely to be a function of the local expression of "downstream effector" molecules, but their coordinate expression must be regulated by transcription factors, some of which may be members of the homeobox gene family. Murine mutations in Hox genes lead to renal agenesis/hypogenesis, which could be related to defective ureteric bud morphogenesis (17). A role for homeobox genes in nephron segmentation is supported by the hepatocyte nuclear factor-1 (HNF-1) knockout, which results in a Fanconi syndrome, due to the lack of expression of a number of proximal tubule transporters (66). There is no obvious reason why the segmentation of the collecting duct and the expression of channels/transporters in specific segments could not also be regulated by homeobox genes. In addition, expression of both hox-B5 and hox-B8 has been observed in the developing lung in a manner consistent with a role in patterning (14, 59, 95).

Growth factors are known to alter the expression of matrix proteins, integrin receptors, proteases that digest matrix and their inhibitors, and in some cases, expression patterns are known to correlate well with morphological changes (9, 11, 27, 41, 64). There is evidence that these gene products may act as "downstream effectors" of branching morphogenesis. For example, during in vitro tubulogenesis induced by EGF receptor ligands, a variety of matrix metalloproteinases are expressed. Production of less branched structures by a combination of HGF and transforming growth factor-beta (TGF-beta ) results in altered ratios of matrix proteases to their inhibitors (MMP1:TIMP1 and UPA:PAI-1) which varies directly with the ratio HGF to TGF-beta (75). Perhaps the most striking finding in the present study is the complex change in the expression of various proteinases that occurs in UB cells in response to BSN-CM including BMP-1, urokinase plasminogen activator receptor, membrane-type metalloproteinase, TIMP-3, protease nexin, serpin, tissue plasminogen activator, serine protease inhibitor 2, and cathepsins B and D. This result is consistent with the notion that arborization of the UB cells (and of the developing collecting system) would be expected to require relatively high local proteolytic activities at leading edges and perhaps lesser, or different, activities in stalk and branch-point regions (60a, 86, 87). The precise role of these and other proteinases and inhibitors in branching morphogenesis will likely be difficult to dissect, given potentially overlapping function and need for localization at a subcellular level.

What mechanism exists to prevent rampant branching and to provide local fine tuning of the process? The finding that BSN-CM leads to the expression of TGF-beta and autocrine motility factor/neuroleukin in UB cells raises the possibility that the mesenchyme-derived soluble factors (or global bipolar gradients of soluble factors in the mesenchyme) that induce branching morphogenesis ultimately activate a mechanism for local control, namely, negative (TGF-beta ) and positive (possibly AMF) autocrine loops. These autocrine factors could affect local ureteric bud branching directly or indirectly by altering mesenchymal expression of matrix proteins (or matrix digesting proteases and their inhibitors) that either facilitate or inhibit branching events by altering the local matrix milieu (78). In addition, two ephrins (A5 and B2) were found to be differentially regulated in this model system. Given the known roles of ephrins and their Eph receptors in axonal guidance and in segmentation of the developing vasculature, it is intriguing to speculate about similar roles in either branching of the collecting system or segmentation of the nephron (25, 97).

The data presented in Fig. 6 and Table 4 demonstrate that this UB cell/BSN-CM model for branching morphogenesis is not only dynamic morphologically (Fig. 1), but also from the standpoint of patterns of gene expression. Different morphologies in the evolution of branching tubular structures correlate with different, although overlapping, patterns of gene expression, suggesting differences in molecular mechanisms underlying the various morphologically distinguished stages. The yz-group is particularly interesting in this regard as these are genes that are upregulated in early and later stages of tubulogenesis and include homeobox genes, ephrins, growth factors and their receptors, and matrix metalloproteinases. In fact, various of these molecular markers correlate with specific morphological stages in the progression from individual cells extending processes through multicellular cords and branching tubules with lumens. Taken together, the expression profiles are consistent with a model in which soluble factors regulate the expression of various transcription factors (e.g., homeobox genes), which in turn alter the expression of distal effector molecules (e.g., proteinases and their inhibitors) and also lead to local autocrine/paracrine control of branching. We are aware that the hypotheses advanced are speculative; however, it should be noted that the gene expression data in this report, and a number functional studies in a variety of systems, is consistent with the plausibility of these hypotheses. We are also aware that cell proliferation and tubulogenesis are intimately linked in this model system; considerable overlap likely exists in both initiating factors as well as effectors. Nevertheless, many of the premises are testable in existing systems. Detailed analysis of spatiotemporal patterns of gene expression during development using in situ hybridization and immunohistochemistry can be used to support or argue against many of the ideas presented here, and perturbation of gene function in tubulogenesis cell culture systems, organ culture based systems, and engineered mutant mice will help evaluate the functional roles of various gene families in branching morphogenesis. Degeneracy may prove a confounding factor in knockout studies; however, once these animals are analyzed in sufficient detail, an upregulated molecule with overlapping function may be identified, and a double knockout might give a more clear-cut answer. Simple in vitro systems, such as the in vitro tubulogenesis cell culture models, may give less ambiguous answers with respect to function, but the advantage of their simplicity is counterbalanced by the fact that they are not embryonic kidneys. Thus these methods, as well as embryonic kidney organ culture and its variants, should be viewed as complementary to furthering our understanding of branching morphogenesis.


    ACKNOWLEDGEMENTS

This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases Grants DK-02392 (to R. O. Stuart) and DK-49517 (to S. K. Nigam). S. K. Nigam is an Established Investigator of the American Heart Association. M. Pohl was supported by the Deutsche Forschungsgemeinschaft.


    FOOTNOTES

A. Pavlova and R. O. Stuart contributed equally to this work.

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact.

Address for reprint requests and other correspondence: R. O. Stuart, Division of Nephrology-Hypertension, University of California, San Diego, 9500 Gilman Drive-0693, La Jolla, CA 92093-0693. (E-mail: rostuart{at}ucsd.edu).

Received 5 February 1999; accepted in final form 7 May 1999.


    REFERENCES
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
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