Density of cells in human tissues?

Density of cells in human tissues?

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Where can I find values, or estimates, of the density of cells in human tissues? Maybe an overall estimate, or distinct values for distinct tissues? Or maybe not human, but mammal tissues (which should be similar)?

Well, Sender, Fuchs, and Milo wrote a paper to discuss the total number of cells in the body and compare it to the number of bacteria in the body ( Their discussion is quite in-depth.

There are a number of ways to calculate it, but an interesting one involved calculating mammalian cell density by a study measuring the DNA obtained from a 25 g mouse. Researchers were able to determine there were 3*109 cells in the mouse (Baserga, 1985). From this study we can simply divide to find a value for "typical" mammalian cell density--1.2*108 cells/g.

If you want to know the number of cells per mL, you'll need the density (g/mL) of the tissue you are measuring. As the comments have mentioned, this is typically around 1 g/mL and varies from person to person. There is a web page that has some tissue densities for various tissues.

Baserga, R. (1985). The Biology of Cell Reproduction (Harvard University Press).

The 'cleanest' data I am aware of is on studies using density gradient centrifugation. In density gradient centrifugation, a preparation of cells is layered on top of a density gradient media which has higher density than water (water=1g/ml). Centrifugation forces denser cells through the media whereas cells with equal or lower density remain above the solution. Common values of gradients are 1.084g/ml, 1.077g/ml and 1.073g/ml but a useful overview of the technique can be found here. According to a manual for one density gradient product, Ficoll-Paque PREMIUM (search the GE website), GE Lifesciences says:

Ficoll-Paque PREMIUM 1.073 can be used when isolating lower density human mononuclear cells, for example mesenchymal stromal/stem cells or monocytes. The higher density lymphocytes and granulocytes will sediment through Ficoll-Paque PREMIUM 1.073 to the bottom of the tube, thereby enriching the lower density cells at the interface. Ficoll-Paque PREMIUM 1.073 has been found superior to Ficoll-Paque PREMIUM for isolating mesenchymal stem cells from human bone marrow (56).

Ficoll-Paque PREMIUM 1,084 can be used for preparation of cell fractions including higher density human mononuclear cells or for isolating lymphocytes that form rosettes with autologous red blood cells (15). It can also be used for separating blood cells from mice and rats, since the lymphocytes in rodents have a slightly higher average density than lymphocytes in humans (50, 51).

If you wanted to try and evaluate density of isolated cells within 'solid' tissues your results would require careful (often enzymatic) release of cells from their integral contact with the extracellular matrix and other cells. I also presume you could try chunks of tissue.

Density gradient centrifugation can also be performed by layering proportions of gradient media of two densities, resulting in a continuous gradient and more nuanced separation.

TL;DR blood cells are slightly denser than water.

hi guys im new here and i was reading this and would add my own believs to this. and most wont follow this, but… Density is a meassure of complexity. Density equals energy + information. Based on our human build up its only logical our body density is close to that of water but with natural selection law of living things and the reproducing factor of non living things such as stars and galaxy's, i have come to conclude that the thing to understand behind it all is that there is that process, that something that drives energy or matter to change into something else, energy(or equal in matter) + information, that something is the next wheel in our understanding.

Engineering microenvironment for human cardiac tissue assembly in heart-on-a-chip platform

A new, plastic, heart-on-a-chip platform capable of continuous non-invasive monitoring of the active force and passive tension.

Intermediate seeding density results in a highly aligned cardiac tissue with minimal cell input.

Cardiac fibroblasts and mesenchymal stem cells are equally effective as a supporting cell population for cardiac tissue formation.

Slower ramp-up of frequency of electrical conditioning (1 Hz/week) is more beneficial than a faster ramp-up (0.2 Hz/day).

Fibrin hydrogel enhances cardiac structure in organ-on-a-chip platform compared to the collagen hydrogel.

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Organ and Histotypic Culture (With Diagram)

Read this article to learn about the organotypic model. The organotypic model consists of three approaches for the original structural and functional interactive relationships of the organ.

The three approaches are: (1) Organ Cultures (2) Histotypic Cultures and (3) Organotypic Cultures.

The cell cultures are widely used in the laboratories world over for various purposes. In vitro studies with isolated cells are useful for understanding of many cell functions such as transcription, translation, cell proliferation, respiration and glycolysis. Thus for the study of biology and many functions, the cells grown in conventional and monolayer cultures may be adequate.

However, for the study of integrated cellular functions or organ functions, isolated cells will be not be of much use, as explained below:

Cellular Interactions in Organ Functions:

There occurs interaction among various cells in vivo, resulting in a cascade of events. These cellular interactions (mostly due to hormonal stimulation) are very important for the expression of their functions, as indicated by the following examples.

a. Hormonal stimulation of fibroblasts is responsible for the release of surfactant by the lung alveolar cells.

b. Androgen binding to stromal cells stimulates prostate epithelium.

Besides hormones, nutritional factors and xenobiotic also exert stimulatory effects on the cells to function in a coordinated fashion.

Organotypic Models:

The cellular interactions that occur in the in vivo system are not possible with isolated cells. The recent developments in the organ and histotypic cultures focus to create in vitro models comparable (as far as possible in biology and functions) to the in vivo systems. The purpose of this organotypic models is to retain the original structural and functional interactive relationships of the organ.

There are three broad approaches in this direction:

The whole organs or small fragments of the organs that retain the special and intrinsic properties are used in culture.

2. Histotypic cultures:

The cell lines grown in three dimensional matrix to high density represent histotypic cultures.

3. Organotypic cultures:

In this case, the cells from different lineages are put together in the desired ratio and spatial relationships to create a component of an organ in the laboratory.

1. Organ Cultures:

The use of organ cultures (organs or their representative fragments) with reference to structural integrity, nutrient and gas exchange, growth and differentiation, along with the advantages and limitations is briefly described.

Structural Integrity:

As already stated, the isolated cells are individual, while in the organ culture, the cells are integrated as a single unit. The cell to cell association, and interactions found in the native tissues or organs are retained to a large extent. As the structural integrity of the original tissue is preserved, the associated cells can exchange signals through cell adhesion or communications.

Nutrient and Gas Exchange:

There is no vascular system in the organ culture. This limits the nutrient supply and gas exchanges of the cells. This happens despite the adequate care taken in the laboratory for the rapid diffusion of nutrients and gases by placing the organ cultures at the interface between the liquid and gaseous phases.

As a consequence, some degree of necrosis at the central part of the organ may occur. Some workers prefer to use high O2 concentration (sometimes even pure O2) in the organ cultures. Exposure of cells to high O2 content is associated with the risk of O2 induced toxicity e.g. nutrient metabolite exchange is severely affected.

Growth and Differentiation:

In general, the organ cultures do not grow except some amount of proliferation that may occur on the outer cell layers.

Advantages of Organ Cultures:

i. Provide a direct means of studying the behaviour of an integrated tissue in the laboratory.

ii. Understanding of biochemical and molecular functions of an organ/tissue becomes easy.

Limitations of Organ Cultures:

i. Organ cultures cannot be propagated, hence for each experiment there is a need for a fresh organ from a donor.

ii. Variations are high and reproducibility is low.

iii. Difficult to prepare, besides being expensive.

Techniques of Organ Culture:

The most important requirement of organ or tissue culture is to place them at such a location so that optimal nutrient and gas exchanges occur.

This is mostly achieved by keeping the tissue at gas- limited interface of the following supports:

v. Strip of Perspex or Plexiglas.

In recent years, filter-well inserts are in use to attain the natural geometry of tissues more easily.

Procedure for Organ Culture:

The basic technique of organ culture consists of the following stages:

1. Dissection and collection of the organ tissue.

2. Reduce the size of the tissue as desired, preferably to less than I mm in thickness.

3. Place tissue on a support at the gas medium interface.

4. Incubate in a humid CO2 incubator.

5. Change the medium (M199 or CMRL 1066) as frequently as desired.

6. The organ culture can be analysed by histology, autoradiography and immunochemistry.

Organ Culture on Stainless Steel Support Grid:

Small fragments of tissue can be cultured on a filter laid on top of a stainless steel grid (Fig. 40.1).

Organ Culture on Filter-well Inserts:

Filter-well inserts have become very popular for organ cultures. This is mainly because the cellular interaction, stratification and polarization are better in these culture systems. Further, the recombination of cells to form tissue — like densities, and access to medium and gas exchange are better.

The four different types of filter wells for growing tissues in the form of cell layers are depicted in Fig. 40.2.

i. Growth of cell layer on top of filter (Fig. 40.2A).

ii. Growth of cell layers on matrix (collagen or matrigel) on top of filter (Fig. 40.2B).

iii. Cell layers grown on the interactive cell layers placed on the underside of filter (Fig. 40.2C).

iv. Cell layer grown on the matrix with interactive cell layer on the underside of the filter (Fig. 40.2D).

Filter well-inserts with different materials (ceramic, collagen, and nitrocellulose) are now commercially available for use in culture laboratories.

Filter-well inserts have been successfully used to develop functionally integrated thyroid epithelium, stratified epidermis, intestinal epithelium and renal (kidney) epithelium.

2. Histotypic Cultures:

Growth and propagation of cell lines in three- dimensional matrix to high cell density represent histotypic cultures. The advantage with this culture system is that dispersed monolayer cultures can be used to regenerate tissue-like structures. The commonly used techniques in histotypic cultures use gel and sponge hollow fibers and spheroids.

Gel and Sponge Technique:

The cells (normal or tumor) in culture can penetrate gels (collagen) or sponges (gelatin) which provides a matrix for morphogenesis of primitive cells. This approach has been used for the development of mammary epithelium, and some tubular and glandular structures.

Hollow Fibers Technique:

In recent years, perfusion chambers with a bed of plastic capillary fibers have been developed. The advantage of using hollow fibers in histotypic cultures is that nutrient and gas exchange is more efficient. As the cells attached to capillary fibers grow, there occurs an increase in cell density to form tissue-like structures.

Many workers claim that the behaviour of high-density cells formed on hollow fibers is comparable to their in vivo behaviour. For instance, choriocarcinoma cells grown in hollow fiber cultures release more chorionic gonadotrophin than in a conventional monolayer. Hollow fiber culture techniques are regarded as ideal systems for the industrial production of several biologically important compounds. Work is progressing in this direction.

Three Dimensional Cultures:

Spheroids in Histotypic Culture:

Spheroids represent the clusters of cells usually formed by the re-association of dissociated cultured cells. It is known for some years that the dissociated embryonic cells reassemble to form a specialized structure. The basic principle of using spheroids in histotypic culture is that the cells in heterotypic or bomotypic aggregates are capable of sorting out themselves into groups to form tissue-like architecture. The major drawback of spheroids is the limitation in the diffusion and exchange of nutrients and gases.

Multicellular Tumor Spheroids (MCTS):

Multicellular tumor spheroids provide an in vitro proliferating model for studies on tumor cells. The three dimensional structure of MCTS allows the experimental studies related to drug therapy, penetration of drugs, resistance to radiation etc.

Further, MCTS have also been used to study several biological processes:

i. Regulation of cell proliferation and differentiation.

The main advantage of three dimensional cell cultures (in the form of MCTS) is that they provide a well-defined geometry of cells planar or spherical which is directly related to the structure and function. It is now well accepted that the MCTS behave like the initial avascular stages of solid tumors in vivo. However, beyond a critical size (≥ 500 mm), most of the MCTS develop necrosis (death of cells) at the centre surrounded by viable cells. A diagrammatic representation of MCTS in comparison with tumor is depicted in Fig. 40.3.

Technique of MCTS production:

Single-cell suspension obtained from trypsinized monolayer cells or disaggregated tumor is inoculated into the medium in magnetic stirrer flasks or roller tubes. As the incubation is carried out for about 3-5 days, aggregates of cells representing spheroids are formed. It is observed that spheroid formation is more efficient under static conditions on stationary and non-adhesive surfaces. For this reason, agar/agarose-coated culture dishes to which cells do not adhere are frequently used to initiate spheroid formation.

Once the spheroids are formed, they are transferred to 24 well plates for analysis. Spheroid growth is quantified by measuring their diameters regularly. This can be done by using a microscope eyepiece micrometer or an image analysis scanner. Good growth of spheroids is observed when grown in wells.

Transfectant mosaic spheroids:

It is now possible to produce spheroids from cells that have been transfected with different genes. Mosaic spheroids are formed by mixing transfected and non-transfected spheroids in the desired proportion.

MCTS can be produced from heterogenous cells also, forming MCTS co- cultures. This is comparable to heterologous spheroids (in short heterospheroids) consisting of tumor cells in combination with host cells.

Some of the MCTS co-cultures are listed:

iii. MCTS and endothelial cells.

Heterospheroids with heterotypic cell interaction serve as good models for studying several in vivo processes e.g. inflammation. MCTS co-cultures are very useful in tissue modelling and tissue engineering, the details of which are given later.

Applications of Spheroids or MCTS:

Spheroids have a wide range of applications. Some of the important ones are listed:

i. Serve as models for a vascular tumor growth.

ii. For the study of gene expression in a three dimensional configuration of cells.

iii. To determine the effect cytotoxic drugs, antibodies, radio nucleotides used for therapeutic purposes.

iv. To study certain disease processes e.g. rheumatoid arthritis.

v. For the development of gene therapies for several diseases e.g. cancer.

vi. To evaluate radiation effects on target tissues.

vii. For the development of tissues and tissue models.

3. Organotypic Cultures:

Organotypic culture basically involves the combination of cells from different lineages in a determined ratio to create a component of an organ. With the advances in the organotypic culture techniques, it is now possible to develop certain tissues or tissue models.

i. Skin equivalents have been created by co-culturing dermis with epidermis with interviewing layers of collagen.


Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes—which is most clearly seen in blood—though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes.

Gene expression is the key determinant of cellular phenotype, and genome-wide expression analysis has been a mainstay of genomics and biomedical research, providing insights into the molecular events underlying human biology and disease. Whereas expression data sets from tissues/primary cells (1, 2) and individuals (3) have accumulated over recent years, only limited expression data sets have allowed analysis across tissues and individuals simultaneously (4). The Genotype-Tissue Expression Project (GTEx) is developing such a resource (5, 6), collecting multiple “nondiseased” tissues sampled from recently deceased human donors. We analyzed the GTEx pilot data freeze (6), which comprised RNA sequencing (RNA-seq) from 1641 samples from 175 individuals representing 43 sites: 29 solid organ tissues, 11 brain subregions, whole blood, and two cell lines: Epstein-Barr virus–transformed lymphocytes (LCL) and cultured fibroblasts from skin [table S1 and (7)].

The identification and characterization of genetic variants that are associated with gene expression are extensively discussed in (6). Here we use the GTEx data to investigate the patterns of transcriptome variation across individuals and tissues and how these patterns associate with human phenotypes. RNA-seq performed on the GTEx pilot samples produced an average of 80 million paired-end mapped reads per sample (fig. S1) (7, 8). We used the mapped reads to quantify gene expression using Gencode V12 annotation (9), which includes 20,110 protein-coding genes (PCGs) and 11,790 long noncoding RNAs (lncRNAs). Comparison with microarray-based quantification for a subset of 736 samples showed concordance between the two technologies (average correlation coefficient = 0.83, fig. S2). At the threshold defined for expression quantitative trait loci (eQTL) analysis [reads per kilobase per million mapped reads (RPKM) > 0.1, see (7)], at which 88% of PCGs and 71% of lncRNAs are detected in at least one sample, the distribution of gene expression across tissues is U-shaped and complementary between PCGs (generally ubiquitously expressed) and lncRNAs (typically tissue-specific or not expressed, Fig. 1A).

(A) Gene expression levels and number of tissues in which genes are expressed (>0.1 RPKM in at least 80% of the samples). RPKMs are averaged over all genes expressed in a given number of tissues. (B) Sample and tissue similarity on the basis of gene expression profiles. Left: Multidimensional scaling Right: Tissue hierarchical clustering. (C) Expression values from eight GTEx tissues (colored circles) plotted radially along seven metagenes extracted from expression data. Antemortem samples curated from the Gene Expression Omnibus (GEO) cluster strongly with GTEx tissues. (D) Transcriptome complexity. Bottom: Cumulative distribution of the average fraction of total transcription contributed by genes when sorted from most-to-least expressed in each tissue (x axis). Lines represent mean values across samples of the same tissue, and lighter-color surfaces around the mean represent dispersion calculated as the standard deviation divided by the cumulative sum of all means. Top: Biological type and relative contribution to total transcription of the hundred most expressed genes. Height of the bars is proportional to the fraction that these genes contribute to total transcription.

Tissues show a characteristic transcriptional signature, as revealed by multidimensional scaling, of both PCG and lncRNA expression (figs. 1B, S3, and S4), with individual phenotypes contributing little (fig. S5). The primary separation, as observed in prior studies (10), is between nonsolid (blood) and solid tissues and, within solid tissues, brain is the most distinct. Brain subregions are not well differentiated, with the exception of cerebellum (fig. S6). Postmortem ischemia appears to have little impact on the characteristic tissue transcriptional signatures, as previously noted (11). In a comparison of 798 GTEx samples with 609 “nondiseased” samples obtained from living (surgical) donors (table S2), we found that GTEx samples clustered with surgical samples of the same tissue type (Fig. 1C and table S3) (12).

Tissue transcription is generally dominated by the expression of a relatively small number of genes. Indeed, we found that for most tissues, about 50% of the transcription is accounted for by a few hundred genes (13). In many tissues, the bulk of transcription is of mitochondrial origin (Fig. 1D and table S4) (14). In kidney, for instance, a highly aerobic tissue with many mitochondria, a median of 51% (>65% in some samples) of the transcriptional output is from the mitochondria (fig. S7). Other tissues show nuclear-dominated expression in blood, for example, three hemoglobin genes contribute more than 60% to total transcription. Genes related to lipid metabolism in pancreas, actin in muscle, and thyroglobulin in thyroid are other examples of nuclear genes contributing disproportionally to tissue-specific transcription. Because RNA samples are generally sequenced to the same depth, in tissues where a few genes dominate expression, fewer RNA-seq reads are comparatively available to estimate the expression of the remaining genes, decreasing the power to estimate expression variation. These tissues—i.e., blood, muscle, and heart (Fig. 1E)—are, consequently, those with less power to detect eQTLs (6). Because most eQTL analyses are performed on easily accessible samples, such as blood, this highlights the relevance of the GTEx multitissue approach.

Although thousands of genes are differentially expressed between tissues (fig. S8) or show tissue-preferential expression (fig. S9 and table S5), fewer than 200 genes are expressed exclusively in a given tissue (figs. S10 and S11 and tables S6 and S7, A to E). The vast majority (

95%) are exclusive to testis and many are lncRNAs. This may reflect low-level basal transcription common to all cell types or result from general tissue heterogeneity, with few primary cell types being specific to a given tissue.

Expression of repetitive elements also recapitulates tissue type (table S8 and fig. S12A). We identified 3046 PCGs whose expression, in at least one tissue, was correlated with the expression of the closest repeat element (on average 2827 base pairs away, fig. S12B). In about half of these cases, the repeat was also significantly coexpressed with other repeats of its same family (table S8 and fig. S13). LncRNA expression can be regulated by specific repeat families (15), and we found evidence that testis-specific expression could be regulated by endogenous retrovirus L repeats (ERVL and ERVL-MaLR) (fig. S12C).

Using linear mixed models, we found that variation in gene expression is far greater among tissues (47% of total variance in gene expression) than among individuals (4% of total variance, Fig. 2A and table S9), and very similar for PCGs and lncRNAs when controlling for gene expression (Fig. 2A). Genes that show high expression variance across individuals and low variance across tissues include genes on the sex chromosomes, as well as autosomal genes, such as the RHD gene that determines Rh blood group.

(A) Left: Contribution of tissue and individual to gene expression variation of PCGs and lncRNAs. Bottom right: Mean ± SD over all genes (filled circles) and over genes with similar expression levels in PCGs and lncRNAs (unfilled circles). Circle size is proportional to the sum of tissue and individual variation, and segment length corresponds to 0.5 SD. Top right: genes with high individual variation and low tissue variation. (B) Sex differentially expressed genes. Top: differentially expressed genes (FDR < 0.05) sorted according to expression differences between males and females. Genes in the Y chromosome are sorted according to the expression in males. Bottom: MMP3 gene expression in males and females. (C) Genes differentially expressed with ethnicity. Top: differentially expressed genes (FDR < 0.05) between African Americans (AA) and European Americans (EA) sorted according to expression differences. A few of these genes lie in regions reported to be under positive selection in similar populations. Bottom: expression of RP11-302J23.1. (D) Genes differentially expressed with age. Top: Genes sorted according to the regression coefficient. Bottom: expression of EDAR2 gene in nerve and artery as a function of age. Shaded area around the regression line represents 95% confidence interval.

We identified 92 PCGs and 43 lncRNAs with global sex-biased expression [false discovery rate (FDR) < 0.05, Fig. 2B and table S10]. Genes overexpressed in males are predominantly located on the Y chromosome. Conversely, many genes on the X chromosome are overexpressed in females, suggesting that more genes might escape X inactivation than previously described (16). Among these, we found XIST and JPX, known to participate in X inactivation, as well as the lncRNAs RP11-309M23.1 and RP13-216E22.4, the expression of which shows enrichment in the nucleus in female cell lines from ENCODE (17) and hence could be candidates to also participate in X inactivation (fig. S14) (16). Among autosomal PCGs, MMP3, linked to susceptibility to coronary heart disease [Online Mendelian Inheritance in Man (OMIM) no. 614466] and more prevalent in males, shows the strongest expression bias (Fig. 2B).

We detected 221 PCGs and 153 lncRNAs globally differentially expressed between individuals of European and African-American ancestry (FDR < 0.05, Fig. 2C and table S11). There is a slight enrichment of lncRNAs (P < 1 × 10 −6 ), among which we identified the RP11-302J23.1 gene, highly expressed in cardiac tissue in African Americans only, and located in a region that harbors weak associations to heart disease (18). Additionally, some genes showing differential expression by ethnicity lie in genomic regions under positive selection in European or sub-Saharan African populations (Fig. 2C and fig. S15).

Finally, we detected 1993 genes that globally change expression with age (FDR < 0.05, Fig. 2D and table S12). Genes that decrease expression are enriched in functions and pathways related to neurodegenerative diseases such as Parkinson’s and Alzheimer’s diseases, among which eight harbor single-nucleotide polymorphisms (SNPs) for these diseases identified from genome-wide association studies (P < 0.05). Among the genes that increase expression with age is EDA2R, whose ligand, EDA, has been associated with age-related phenotypes (19).

We also identified 753 genes with tissue specific sex-biased expression (FDR < 0.05, table S13) predominantly in breast tissue (92%), and 31 genes with tissue-specific ethnicity-biased expression, many in the skin (FDR < 0.05, Table 1 and table S14). Among the sex-differentially expressed genes, five show biased expression specifically in heart and are of interest given the differing prevalence of cardiovascular disease between males and females. One of these genes, PLEKHA7 (fig. S15C), contains SNPs associated with risk for cardiovascular disease.

Differentially expressed genes between males (M) and females (F) and between African American (AA) and European American (EA) in those tissues with at least 10 samples per group. Median fold change (on autosomal genes) was calculated for tissues with more than two significant genes.

Overall, tissue specificity is likely to be driven by the concerted expression of multiple genes. Thus, we performed sex-based differential analysis of coexpression networks. We identified 42 coexpression modules in males and 46 in females (fig. S16). Among male-specific modules, we found one related to spermatid differentiation and development (FDR = 9.0 × 10 −4 , fig. S16B), and among female-specific modules, we found one related to epidermis and ectoderm development (FDR = 4.6 × 10 −14 , fig. S16C). Differential network expression, therefore, distinguishes differences between male and females not well captured by analysis of individual genes.

Split-mapped RNA-seq reads predict about 87,000 novel junctions with very strong support (fig. S17). These tend to be more tissue specific, detected in fewer samples, and less conserved than previously annotated junctions (only 2.6% of novel junctions can be detected as orthologous in mouse, compared to 65% for annotated junctions). Multidimensional scaling based on exon inclusion levels again largely recapitulates tissue type (Fig. 3A). However, samples from brain cluster as the primary out-group, supporting the existence of a distinct splicing program in the brain (20). Furthermore, preferential gene expression of RNA-binding proteins and both differential and preferential exon inclusion are enriched in the brain (figs. S18 and S19 and table S15). We found very few exons exclusively included or excluded in a given tissue (fig. S20 and table S16), 40% of which show exclusive inclusion in the brain. We also found that micro-exons (<15 bp) are overwhelmingly used in the brain compared to other tissues (Wilcoxon test, P < 1 × 10 −7 , Fig. 3B). This pattern is not obvious in short exons longer than 15 bp (P = 0.3, fig. S21). This observed brain-specific splicing pattern may result from differential splicing in the cerebellum, because expression clustering of the brain regions reveals a general up-regulation of RNA-binding proteins specifically in the cerebellum (Fig. 3C). This is also the brain region exhibiting the largest proportion of novel splicing events (fig. S22).

(A) Multidimensional scaling of all samples on the basis of exon inclusion levels (Percent spliced in, PSI). (B) Microexon inclusion across tissues. Values of tissue exon inclusion close to 1 (–1) indicate that the microexon is included (excluded), in nearly all samples from the tissue, and excluded (included) in nearly all samples from the rest of the tissues. Tissues are sorted according to tissue exon inclusion (phi) median value. (C) Clustering of brain samples on the basis of the normalized expression levels of 67 RNA binding proteins involved in splicing. The order of samples and genes is obtained by biclustering the expression matrix. (D) Left: Contribution of tissue and individual to splicing variation in PCGs. Bottom right: Mean ± SD of individual and tissue contributions to splicing and to gene expression variation. Circle size is proportional to the sum of tissue and individual variation and segment length corresponds to 0.5 SD. Top right: Genes with high splicing variation across individuals. (E) Contribution of gene expression to the between-individual and between-tissue variation in isoform abundance

In contrast to gene expression, variation of splicing, measured either from relative isoform abundance or exon inclusion, is similar across tissues and across individuals, but exhibits a much larger proportion of residual unexplained variation (Fig. 3D, fig. S23, and table S17). This could arise from nonadditive interactions between individuals and tissues, but might also reflect stochastic, nonfunctional fluctuations that are more common in splicing than in expression (21). Among the genes that show high interindividual splicing variability, we found an enrichment of ribosomal proteins and genes related to translation and protein biosynthesis (Fig. 3D and table S18). Higher variability between individuals may also partially reflect an effect of ischemic time on splicing, which we observed when clustering samples by exon inclusion within each tissue (fig. S24).

The abundance of splicing isoforms reflects the actions of both primary transcription and posttranscriptional processing—mostly alternative splicing. To determine the relative contribution of each process, we estimated the proportion of variance in isoform abundance that can be simply explained by variance in gene expression. We found that gene expression explains only 45% of the variance between individuals, but 84% of the variance between tissues (Fig. 3E and fig. S25). This strongly suggests that primary transcription is the main driver of cellular specificity, with splicing playing a complementary role. Although this may be unexpected, given the magnitude of the effect, it is consistent with recent findings of low proteomic support for alternatively spliced isoforms (22) and few shifts in major protein isoforms across cell types (table S19) (23).

Overall, our results underscore the value of monitoring the transcriptome of multiple tissues and individuals in order to understand tissue-specific transcriptional regulation and to uncover the transcriptional determinants of human phenotypic variation and disease susceptibility.


tissue typing identification of tissue types for purposes of predicting acceptance or rejection of grafts and transplants . The process and purposes of tissue typing are essentially the same as for blood typing. The major difference lies in the kinds of antigens being evaluated. The acceptance of allografts depends on the hla antigens (HLA) if the donor and recipient are not HLA identical, the allograft is rejected, sometimes within minutes. The HLA genes are located in the major histocompatibility complex , a region on the short arm of chromosome 6, and are involved in cell-cell interaction, immune response , organ transplantation, development of cancer, and susceptibility to disease. There are five genetic loci, designated HLA-A, HLA-B, HLA-C, HLA-D, and HLA-DR. At each locus, there can be any of several different alleles.

Each person inherits one chromosome 6 from the mother and one from the father that is, each parent transmits to the child one allele for each kind of antigen (A, B, C, D, and DR). If the parents are different at both alleles of a locus, the statistical chance of one sibling being identical to another is one in four (25 per cent), the chance of being identical at one allele only (half-identical) is 50 per cent, and the chance of a total mismatch is 25 per cent.

Techniques for Tissue Typing . Histocompatibility testing involves several basic methods of assay for HLA differences. The most widely used method uses the polymerase chain reaction to compare the DNA of the person, organ, or graft being tested with known pieces of the genes encoding MHC antigens. The variability of these regions of the genes determines the tissue type of the subject.

Serologic methods are used to detect serologically defined antigens on the surfaces of cells. In general, HLA-A, -B, and -C determinants are primarily measured by serologic techniques. A second method, involving lymphocyte reactivity in a mixed lymphocyte culture, for determining HLA-D or lymphocyte-defined antigens, is now only rarely used.

Essentially, the serologic method is performed by incubating target lymphocytes (isolated from fresh peripheral blood) with antisera that recognize all known HLA antigens. The cells are spread in a tray with microscopic wells containing various kinds of antisera and are incubated for 30 minutes, followed by an additional 60-minute complement incubation. If the lymphocytes have on their surfaces antigens recognized by the antibodies in the antiserum, the lymphocytes are lysed. A dye is added to show changes in the permeability of the cell membrane and cellular death. The proportion of cells destroyed by lysis indicates the degree of histologic incompatibility. If, for example, the lymphocytes from a person being tested for HLA-A3 are destroyed in a well containing antisera for HLA-A3, the test is positive for this antigen group.

Data availability

High-resolution images corresponding to immunohistochemically stained TMA cores (using both antibodies) from 44 different tissue types, as well as the lung cohort of 360 individuals and whole slide images of bronchus, nasal mucosa and eye tissue are available in the BioStudies repository ( under the accession S-BSST421. The normalized consensus transcript expression levels based on transcriptomics data from HPA, GTEx, and FANTOM5 are readily available under the download page in the latest version 19.3 of the Human Protein Atlas (

A swifter way towards 3D-printed organs

(CAMBRIDGE, Mass.) — 20 people die every day waiting for an organ transplant in the United States, and while more than 30,000 transplants are now performed annually, there are over 113,000 patients currently on organ waitlists. Artificially grown human organs are seen by many as the “holy grail” for resolving this organ shortage, and advances in 3D printing have led to a boom in using that technique to build living tissue constructs in the shape of human organs. However, all 3D-printed human tissues to date lack the cellular density and organ-level functions required for them to be used in organ repair and replacement.

Living embryoid bodies surround a hollow vascular channel printed using the SWIFT method. Credit: Wyss Institute at Harvard University

Now, a new technique called SWIFT (sacrificial writing into functional tissue) created by researchers from Harvard’s Wyss Institute for Biologically Inspired Engineering and John A. Paulson School of Engineering and Applied Sciences (SEAS), overcomes that major hurdle by 3D printing vascular channels into living matrices composed of stem-cell-derived organ building blocks (OBBs), yielding viable, organ-specific tissues with high cell density and function. The research is reported in Science Advances.

“This is an entirely new paradigm for tissue fabrication,” said co-first author Mark Skylar-Scott, Ph.D., a Research Associate at the Wyss Institute. “Rather than trying to 3D-print an entire organ’s worth of cells, SWIFT focuses on only printing the vessels necessary to support a living tissue construct that contains large quantities of OBBs, which may ultimately be used therapeutically to repair and replace human organs with lab-grown versions containing patients’ own cells.”

SWIFT involves a two-step process that begins with forming hundreds of thousands of stem-cell-derived aggregates into a dense, living matrix of OBBs that contains about 200 million cells per milliliter. Next, a vascular network through which oxygen and other nutrients can be delivered to the cells is embedded within the matrix by writing and removing a sacrificial ink. “Forming a dense matrix from these OBBs kills two birds with one stone: not only does it achieve a high cellular density akin to that of human organs, but the matrix’s viscosity also enables printing of a pervasive network of perfusable channels within it to mimic the blood vessels that support human organs,” said co-first author Sébastien Uzel, Ph.D., a Research Associate at the Wyss Institute and SEAS.

The cellular aggregates used in the SWIFT method are derived from adult induced pluripotent stem cells, which are mixed with a tailored extracellular matrix (ECM) solution to make a living matrix that is compacted via centrifugation. At cold temperatures (0-4 °C), the dense matrix has the consistency of mayonnaise – soft enough to manipulate without damaging the cells, but thick enough to hold its shape – making it the perfect medium for sacrificial 3D printing. In this technique, a thin nozzle moves through this matrix depositing a strand of gelatin “ink” that pushes cells out of the way without damaging them.

A branching network of channels of red, gelatin-based “ink” is 3D printed into a living cardiac tissue construct composed of millions of cells (yellow) using a thin nozzle to mimic organ vasculature. Credit: Wyss Institute at Harvard University

When the cold matrix is heated to 37 °C, it stiffens to become more solid (like an omelet being cooked) while the gelatin ink melts and can be washed out, leaving behind a network of channels embedded within the tissue construct that can be perfused with oxygenated media to nourish the cells. The researchers were able to vary the diameter of the channels from 400 micrometers to 1 millimeter, and seamlessly connected them to form branching vascular networks within the tissues.

Organ-specific tissues that were printed with embedded vascular channels using SWIFT and perfused in this manner remained viable, while tissues grown without these channels experienced cell death in their cores within 12 hours. To see whether the tissues displayed organ-specific functions, the team printed, evacuated, and perfused a branching channel architecture into a matrix consisting of heart-derived cells and flowed media through the channels for over a week. During that time, the cardiac OBBs fused together to form a more solid cardiac tissue whose contractions became more synchronous and over 20 times stronger, mimicking key features of a human heart.

“Our SWIFT biomanufacturing method is highly effective at creating organ-specific tissues at scale from OBBs ranging from aggregates of primary cells to stem-cell-derived organoids,” said corresponding author Jennifer Lewis, Sc.D., who is a Core Faculty Member at the Wyss Institute as well as the Hansjörg Wyss Professor of Biologically Inspired Engineering at SEAS. “By integrating recent advances from stem-cell researchers with the bioprinting methods developed by my lab, we believe SWIFT will greatly advance the field of organ engineering around the world.”

Tissues created without SWIFT-printed channels display cell death (red) in their cores after 12 hours of culture (left), while tissues with channels (right) have healthy cells. Credit: Wyss Institute at Harvard University

Human Tissue Engineering Company Prellis Biologics Raises $8.7 Million Series A Round Announces First Animal Transplant of Its 3D-Printed Tissue

STRUCTURE TRANSPLANT: Prellis structure transplanted alone is surrounded by single cell walled capillaries within two weeks of transplantation into immunocompetent mouse (left). Human tumor cells transplanted in Prellis structures grow rapidly, are highly vascularized and demonstrate minimal hypoxia (right) (red = CD31, blue = DAPI, green = printed structure) [Press Release Image: Prellis Biologics]

STRUCTURE TRANSPLANT: Prellis structure transplanted alone is surrounded by single cell walled capillaries within two weeks of transplantation into immunocompetent mouse (left). Human tumor cells transplanted in Prellis structures grow rapidly, are highly vascularized and demonstrate minimal hypoxia (right) (red = CD31, blue = DAPI, green = printed structure) [Press Release Image: Prellis Biologics]

ARTERIAL STRUCTURE: Prellis arterial structure in a computer aided design model (left), and printed and grown with vascular endothelial cells (right). (blue = Prellis structure, red = vascular cells labeled with vWF). [Press Release Image: Prellis Biologics]

FLOW CHANNELS: Prellis printed structure that supports flow through independent channels with a 20 micron interface, allowing for study of gas and nutrient exchange as well as cell-cell cross-talk in a system that mimics human physiology. [Press Release Image: Prellis Biologics]

SAN FRANCISCO--( BUSINESS WIRE )--Prellis Biologics today announced that Khosla Ventures has led an $8.7 Series A investment in the company. The announcement comes as Prellis has reached major tissue engineering milestones in its mission to use 3D holographic printing to create 3D tissue and organs for research and transplantation.

Prellis Biologics’ original seed round investors, including True Ventures and Indie Bio (SOSV), joined Khosla in the round. Invested capital in Prellis now totals $10.5 million.

“Regenerative medicine has made enormous leaps in recent decades. However, to create complete organs, we need to build higher order structures like the vascular system,” said Dr. Alex Morgan, Principal at Khosla Ventures. “Prellis’ optical technology provides the scaffolding necessary to engineer these larger masses of tissues. With our investment in Prellis, we’re supporting an initiative that will ultimately produce a functioning lobe of the lung, or even a kidney, to be used in addressing an enormous unmet global need.”

“The holy grail of human tissue engineering is the ability to build complex tissues with working vascular systems,” said Dr. Melanie Matheu, Prellis Biologics’ co-founder and CEO. “The future of regenerative medicine revolves around harnessing the power of our own cells as therapeutics and building the tissues to keep them alive. Khosla Ventures is the perfect investor to support our merging of deep tech and cutting-edge regenerative medicine. With this technology in hand, we can begin to ask questions about real 3D cell biology that have never been asked before.”

Prellis Reports Progress in Tissue Engineering

The new funding coincides with Prellis’ recent advancements in tissue engineering.

First, Prellis Biologics has demonstrated positive results from the first animal transplantation of its 3D tissue scaffolds – called Vascular Tissue Blanks™ – carried out at Stanford University.

Prellis’ transplanted structures support human tumor growth at rates that are similar or better than typical tumor transplant methods, but with fewer cells. “We were excited to see that we could achieve full tumor engraftment and vascularization by transplanting just 200,000 cells. This is an order of magnitude fewer cells, since typical tumor studies in animals require two million or more cells,” said Dr. Matheu. “A breakthrough like this opens the door to studying rare human tumors and complex human tumor immune system reactions. It has the potential to significantly reduce overall animal use and speed up drug discovery efforts.”

A critical finding in the animal studies was confirmation that the laser-printed structures support rapid and extensive vascularization. Within two weeks, Prellis-built scaffolds were populated by 10-micron capillaries that grew spontaneously, even without the presence of pre-seeded cells. Within eight weeks, large, branched vasculature up to 50 microns was identified deep inside of the transplanted structures, indicating the animal’s vasculature system had adopted the scaffolding and incorporated it into its own circulatory system.

“Spontaneous, structurally guided vascularization of our laser-printed structures is a significant milestone on the way to transplanting complex tissues. We’ve demonstrated that we can establish circulation in our transplanted structures,” said Dr. Matheu. “Our team will be compiling the results of these studies for peer review publication later this year.”

Second, Prellis is the first company to deliver biocompatible vascularized tissue blanks to the pharmaceutical and academic markets for advanced 3D tissue culture. Prellis’ Vascular Tissue Blanks are now being used by scientists for research in oncology, tissue development research, neurobiology studies, and drug testing. Over 30 pharmaceutical and academic research labs, including groups at UC San Francisco, Johns Hopkins, UC Irvine, and Memorial Sloan Kettering, are experimenting with the Vascular Tissue Blanks, which allow therapeutics to be tested in consistent and fast-to-set-up models of 3D human tissues for the first time.

“We had been using grow-your-own spheroid techniques, which required intricate setups and were inconsistent in size and morphology, complicating downstream analysis,” said Maria Soloveychik, PhD, CEO of SyntheX. “What changes with Prellis? You just use it. The setup is quick and consistent, and the handling is straightforward.”

Prellis’ Vascular Tissue Blanks reduce time to drug screening in 3D organoids by an estimated 90% relative to other 3D cell culture technologies. The organoids are fully transplantable just a few hours after the cells are added. With the pre-made tissue scaffolds, 3D organoid drug screening results can be achieved in as little as 48 hours. Prellis Biologics is the only company capable of producing high-resolution (< 1 micron) 3D printed structures out of biocompatible hydrogels.

“The tissue blanks are designed to promote oxygenation of high-density cell cultures grown in 3D. We use them in our own laboratory to study organ development. It’s exciting to provide them as a ready-made solution for the 3D cell culture drug screening process. We haven’t found a human cell type that won’t grow on our 3D scaffolds,” said Dr. Matheu.

Third, Prellis has made significant progress in achieving in vitro microfluidic flow through complex vascular channels, with separation as fine as 10–20 microns – a critical precursor to creating complex viable vascularized tissue in the laboratory. Prellis’ R&D team is currently testing 10-20 micron biomaterial interface for cell-cell interactions and nutrient exchange – the first steps in ensuring a functional filtration and gas exchange system, critical building blocks for organ systems such as the lung and kidney.

Ultimately, Prellis Biologics has its sights set firmly on human organ transplantation and expects to initiate its first large animal studies before the end of the year. The first transplanted large tissues Prellis will test are engineered arterial replacements, 3-4 mm in diameter. “Arterial replacements are a natural stepping-stone to production of larger solid organs,” said Dr. Matheu. “The ones we have designed are far more sophisticated than the standard vascular replacements. They are surrounded by fine capillary beds that are known to contribute to the structural integrity and engraftment of arteries after the surgical procedure.”

More information on Prellis Biologics can be found here.

About Prellis Biologics, Inc.

Prellis Biologics, Inc. developed the first holographic printing system able to match and accurately replicate human organ and tissue structures for R&D and organ transplantation. The combined resolution and speed of Prellis Biologics’ printing technology allows for full human organ systems to be created with cell-compatible biomatrices. We are dedicated to solving the global human organ transplant shortage. Prellis Biologics, Inc. was founded in 2016 and is a privately held company based in San Francisco, CA.

Figure 1. Purity and Recovery of Cells from Whole Blood When Using Cost-Effective Lymphoprep™ is Comparable to Using Ficoll-Paque™ PLUS

(A) Density gradient centrifugation of peripheral whole blood using Lymphoprep™ results in similar cell purity of mononuclear cells including T cells, B cells, NK cells and monocytes compared to Ficoll-Paque™ PLUS. (B) The recovery of total mononuclear cells and CD45+ cells is also similar. (n = 5, Mean ± SD).

Figure 2. Purity and Recovery of Cells from Cord Blood When Using Cost-Effective Lymphoprep™ is Comparable to Using Ficoll-Paque™ PLUS

(A) Density Gradient centrifugation of cord blood using Lymphoprep™ results in similar cell purity of mononuclear cells including T cells, B cells, NK cells and monocytes compared to Ficoll-Paque™ PLUS. (B) The recovery of total mononuclear cells and CD45+ cells is also similar. (n = 4, Mean ± SD).

Watch the video: What are Tissues? Dont Memorise (May 2022).