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.

The tumour stroma is an active participant during cancer progression. Stromal cells promote tumour progression and metastasis through multiple mechanisms including enhancing tumour invasiveness and angiogenesis, and suppressing immune surveillance. We report here that miR-126/miR-126*, a microRNA pair derived from a single precursor, independently suppress the sequential recruitment of mesenchymal stem cells and inflammatory monocytes into the tumour stroma to inhibit lung metastasis by breast tumour cells in a mouse xenograft model. miR-126/miR-126* directly inhibit stromal cell-derived factor-1 alpha (Sdf-1α) expression, and indirectly suppress the expression of chemokine (C–C motif) ligand 2 (Ccl2) by cancer cells in an Sdf-1α-dependent manner. miR-126/miR-126* expression is downregulated in cancer cells by promoter methylation of their host gene Egfl7. These findings determine how this microRNA pair alters the composition of the primary tumour microenvironment to favour breast cancer metastasis, and demonstrate a correlation between miR-126/126* downregulation and poor metastasis-free survival of breast cancer patients.

Self-assembling peptides and peptide derivatives have received significant interest for several biomedical applications, including tissue engineering, wound healing, cell delivery, drug delivery, and vaccines. This class of materials has exhibited significant variability in immunogenicity, with many peptides eliciting no detectable antibody responses but others eliciting very strong responses without any supplemental adjuvants. Presently, strategies for either avoiding strong antibody responses or specifically inducing them are not well developed, even though they are critical for the use of these materials both within tissue engineering and within immunotherapies. Here, we investigated the molecular determinants and immunological mechanisms leading to the significant immunogenicity of the self-assembling peptide OVA-Q11, which has been shown previously to elicit strong antibody responses in mice. We show that these responses can last for at least a year. Using adoptive transfer experiments and T cell knockout models, we found that these strong antibody responses were T cell-dependent, suggesting a route for avoiding or ensuring immunogenicity. Indeed, by deleting amino acid regions in the peptide recognized by T cells, immunogenicity could be significantly diminished. Immunogenicity could also be attenuated by mutating key residues in the self-assembling domain, thus preventing fibrillization. A second self-assembling peptide, KFE8, was also non-immunogenic, but nanofibers of OVA-KFE8 elicited strong antibody responses similar to OVA-Q11, indicating that the adjuvant action was not dependent on the specific self-assembling peptide sequence. These findings will facilitate the design of self-assembled peptide biomaterials, both for applications where immunogenicity is undesirable and where it is advantageous.

Biomaterials displaying precise ratios of different bioactive protein components are critical for applications ranging from vaccines to regenerative medicine, but their design is often hindered by limited choices and cross-reactivity of protein conjugation chemistries. Here, we describe a strategy for inducing multiple different expressed proteins of choice to assemble into nanofibers and gels with exceptional compositional control. The strategy employs novel “βTail” tags, which allow for good protein expression in bacteriological cultures, yet can be induced to co-assemble into nanomaterials when mixed with additional β-sheet fibrillizing peptides. Multiple different βTail fusion proteins could be inserted into peptide nanofibers alone or in combination at predictable, smoothly gradated concentrations, providing a simple yet versatile route to install precise combinations of proteins into nanomaterials. The technology is illustrated by achieving precisely targeted hues using mixtures of fluorescent proteins, by creating nanofibers bearing enzymatic activity, and by adjusting antigenic dominance in vaccines.