Combinatorial Tags Research Articles

Spatial epitope barcoding reveals clonal tumor patch behaviors.

Intratumoral heterogeneity is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are still largely unsuitable to accurately track phenotypes and clonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitopes for imaging using combinatorial tagging (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using EpicMIBI, we dissected the spatial component of cell lineages and phenotypes in xenograft models of small cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of clonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in these models. In a tumor model harboring a fraction of PTEN-deficient cancer cells, we observed a non-autonomous increase of clonal patch size in PTEN wild-type cancer cells. EpicMIBI facilitates in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.

Pheniqs 2.0: accurate, high-performance Bayesian decoding and confidence estimation for combinatorial barcode indexing

BackgroundSystems biology increasingly relies on deep sequencing with combinatorial index tags to associate biological sequences with their sample, cell, or molecule of origin. Accurate data interpretation depends on the ability to classify sequences based on correct decoding of these combinatorial barcodes. The probability of correct decoding is influenced by both sequence quality and the number and arrangement of barcodes. The rising complexity of experimental designs calls for a probability model that accounts for both sequencing errors and random noise, generalizes to multiple combinatorial tags, and can handle any barcoding scheme. The needs for reproducibility and community benchmark standards demand a peer-reviewed tool that preserves decoding quality scores and provides tunable control over classification confidence that balances precision and recall. Moreover, continuous improvements in sequencing throughput require a fast, parallelized and scalable implementation.Results and discussionWe developed a flexible, robustly engineered software that performs probabilistic decoding and supports arbitrarily complex barcoding designs. Pheniqs computes the full posterior decoding error probability of observed barcodes by consulting basecalling quality scores and prior distributions, and reports sequences and confidence scores in Sequence Alignment/Map (SAM) fields. The product of posteriors for multiple independent barcodes provides an overall confidence score for each read. Pheniqs achieves greater accuracy than minimum edit distance or simple maximum likelihood estimation, and it scales linearly with core count to enable the classification of > 11 billion reads in 1 h 15 m using < 50 megabytes of memory. Pheniqs has been in production use for seven years in our genomics core facility.ConclusionWe introduce a computationally efficient software that implements both probabilistic and minimum distance decoders and show that decoding barcodes using posterior probabilities is more accurate than available methods. Pheniqs allows fine-tuning of decoding sensitivity using intuitive confidence thresholds and is extensible with alternative decoders and new error models. Any arbitrary arrangement of barcodes is easily configured, enabling computation of combinatorial confidence scores for any barcoding strategy. An optimized multithreaded implementation assures that Pheniqs is faster and scales better with complex barcode sets than existing tools. Support for POSIX streams and multiple sequencing formats enables easy integration with automated analysis pipelines.

Spatial Epitope Barcoding Reveals Subclonal Tumor Patch Behaviors

Intratumoral variability is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are unsuitable to accurately track phenotypes and subclonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitope combinatorial tags (EpicTags), which we coupled to multiplex ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using this platform, we dissected the spatial components of cell lineages and phenotypes in a xenograft model of small-cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of subclonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in this model. In tumors harboring a fraction of PTEN-deficient cancer cells, we uncovered a non-autonomous increase of subclonal patch size in PTEN wild-type cancer cells. EpicMIBI can facilitate in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.

Single-cell mapping of lineage and identity in direct reprogramming.

Direct lineage reprogramming involves the remarkable conversion of cellular identity. Single-cell technologies aid in deconstructing the considerable heterogeneity that emerges during lineage conversion. However, lineage relationships are typically lost during cell processing, complicating trajectory reconstruction. Here, we present ‘CellTagging’, a combinatorial cell indexing methodology, permitting the parallel capture of clonal history and cell identity, where sequential rounds of cell labelling enable the construction of multi-level lineage trees. CellTagging and longitudinal tracking of fibroblast to induced endoderm progenitor (iEP) reprogramming reveals two distinct trajectories: one leading to successfully reprogrammed cells, and one leading to a ‘dead-end’ state, paths determined in the earliest reprogramming stages. We find that expression of a putative methyltransferase, Mettl7a1, is associated with the successful reprogramming trajectory, where its addition to the reprogramming cocktail increases the yield of iEPs. Together, these results demonstrate the utility of our lineage tracing method to reveal dynamics of direct reprogramming.

Orthogonal Protein Purification Facilitated by a Small Bispecific Affinity Tag

Due to the high costs associated with purification of recombinant proteins the protocols need to be rationalized. For high-throughput efforts there is a demand for general methods that do not require target protein specific optimization1 . To achieve this, purification tags that genetically can be fused to the gene of interest are commonly used2 . The most widely used affinity handle is the hexa-histidine tag, which is suitable for purification under both native and denaturing conditions3 . The metabolic burden for producing the tag is low, but it does not provide as high specificity as competing affinity chromatography based strategies1,2.Here, a bispecific purification tag with two different binding sites on a 46 amino acid, small protein domain has been developed. The albumin-binding domain is derived from Streptococcal protein G and has a strong inherent affinity to human serum albumin (HSA). Eleven surface-exposed amino acids, not involved in albumin-binding4 , were genetically randomized to produce a combinatorial library. The protein library with the novel randomly arranged binding surface (Figure 1) was expressed on phage particles to facilitate selection of binders by phage display technology. Through several rounds of biopanning against a dimeric Z-domain derived from Staphylococcal protein A5, a small, bispecific molecule with affinity for both HSA and the novel target was identified6 .The novel protein domain, referred to as ABDz1, was evaluated as a purification tag for a selection of target proteins with different molecular weight, solubility and isoelectric point. Three target proteins were expressed in Escherishia coli with the novel tag fused to their N-termini and thereafter affinity purified. Initial purification on either a column with immobilized HSA or Z-domain resulted in relatively pure products. Two-step affinity purification with the bispecific tag resulted in substantial improvement of protein purity. Chromatographic media with the Z-domain immobilized, for example MabSelect SuRe, are readily available for purification of antibodies and HSA can easily be chemically coupled to media to provide the second matrix.This method is especially advantageous when there is a high demand on purity of the recovered target protein. The bifunctionality of the tag allows two different chromatographic steps to be used while the metabolic burden on the expression host is limited due to the small size of the tag. It provides a competitive alternative to so called combinatorial tagging where multiple tags are used in combination1,7.

Orthogonal Protein Purification Facilitated by a Small Bispecific Affinity Tag

Due to the high costs associated with purification of recombinant proteins the protocols need to be rationalized. For high-throughput efforts there is a demand for general methods that do not require target protein specific optimization1 . To achieve this, purification tags that genetically can be fused to the gene of interest are commonly used2 . The most widely used affinity handle is the hexa-histidine tag, which is suitable for purification under both native and denaturing conditions3 . The metabolic burden for producing the tag is low, but it does not provide as high specificity as competing affinity chromatography based strategies1,2. Here, a bispecific purification tag with two different binding sites on a 46 amino acid, small protein domain has been developed. The albumin-binding domain is derived from Streptococcal protein G and has a strong inherent affinity to human serum albumin (HSA). Eleven surface-exposed amino acids, not involved in albumin-binding4 , were genetically randomized to produce a combinatorial library. The protein library with the novel randomly arranged binding surface (Figure 1) was expressed on phage particles to facilitate selection of binders by phage display technology. Through several rounds of biopanning against a dimeric Z-domain derived from Staphylococcal protein A5, a small, bispecific molecule with affinity for both HSA and the novel target was identified6 . The novel protein domain, referred to as ABDz1, was evaluated as a purification tag for a selection of target proteins with different molecular weight, solubility and isoelectric point. Three target proteins were expressed in Escherishia coli with the novel tag fused to their N-termini and thereafter affinity purified. Initial purification on either a column with immobilized HSA or Z-domain resulted in relatively pure products. Two-step affinity purification with the bispecific tag resulted in substantial improvement of protein purity. Chromatographic media with the Z-domain immobilized, for example MabSelect SuRe, are readily available for purification of antibodies and HSA can easily be chemically coupled to media to provide the second matrix. This method is especially advantageous when there is a high demand on purity of the recovered target protein. The bifunctionality of the tag allows two different chromatographic steps to be used while the metabolic burden on the expression host is limited due to the small size of the tag. It provides a competitive alternative to so called combinatorial tagging where multiple tags are used in combination1,7.

WITHDRAWN: Reprint of: Making the most of affinity tags

Proteins do not naturally lend themselves to high-throughput analysis because of their diverse physiochemical properties. Consequently, affinity tags have become indispensable tools for structural and functional proteomics initiatives. Although originally developed to facilitate the detection and purification of recombinant proteins, in recent years it has become clear that affinity tags can have a positive impact on the yield, solubility and even the folding of their fusion partners. However, no single affinity tag is optimal with respect to all of these parameters; each has its strengths and weaknesses. Therefore, combinatorial tagging might be the only way to harness the full potential of affinity tags in a high-throughput setting.

Extensive association of functionally and cytotopically related mRNAs with Puf family RNA-binding proteins in yeast.

Genes encoding RNA-binding proteins are diverse and abundant in eukaryotic genomes. Although some have been shown to have roles in post-transcriptional regulation of the expression of specific genes, few of these proteins have been studied systematically. We have used an affinity tag to isolate each of the five members of the Puf family of RNA-binding proteins in Saccharomyces cerevisiae and DNA microarrays to comprehensively identify the associated mRNAs. Distinct groups of 40–220 different mRNAs with striking common themes in the functions and subcellular localization of the proteins they encode are associated with each of the five Puf proteins: Puf3p binds nearly exclusively to cytoplasmic mRNAs that encode mitochondrial proteins; Puf1p and Puf2p interact preferentially with mRNAs encoding membrane-associated proteins; Puf4p preferentially binds mRNAs encoding nucleolar ribosomal RNA-processing factors; and Puf5p is associated with mRNAs encoding chromatin modifiers and components of the spindle pole body. We identified distinct sequence motifs in the 3′-untranslated regions of the mRNAs bound by Puf3p, Puf4p, and Puf5p. Three-hybrid assays confirmed the role of these motifs in specific RNA–protein interactions in vivo. The results suggest that combinatorial tagging of transcripts by specific RNA-binding proteins may be a general mechanism for coordinated control of the localization, translation, and decay of mRNAs and thus an integral part of the global gene expression program.