Optimization of a microarray for fission yeast

Bar-code (tag) microarrays of yeast gene-deletion collections facilitate the systematic identification of genes required for growth in any condition of interest. Anti-sense strands of amplified bar-codes hybridize with ~10,000 (5,000 each for up- and down-tags) different kinds of sense-strand probes on an array. In this study, we optimized the hybridization processes of an array for fission yeast. Compared to the first version of the array (11 µm, 100K) consisting of three sectors with probe pairs (perfect match and mismatch), the second version (11 µm, 48K) could represent ~10,000 up-/down-tags in quadruplicate along with 1,508 negative controls in quadruplicate and a single set of 1,000 unique negative controls at random dispersed positions without mismatch pairs. For PCR, the optimal annealing temperature (maximizing yield and minimizing extra bands) was 58℃ for both tags. Intriguingly, up-tags required 3× higher amounts of blocking oligonucleotides than down-tags. A 1:1 mix ratio between up- and down-tags was satisfactory. A lower temperature (25℃) was optimal for cultivation instead of a normal temperature (30℃) because of extra temperature-sensitive mutants in a subset of the deletion library. Activation of frozen pooled cells for >1 day showed better resolution of intensity than no activation. A tag intensity analysis showed that tag(s) of 4,316 of the 4,526 strains tested were represented at least once; 3,706 strains were represented by both tags, 4,072 strains by up-tags only, and 3,950 strains by down-tags only. The results indicate that this microarray will be a powerful analytical platform for elucidating currently unknown gene functions.

Inflammation induces two types of inflammatory dendritic cells in inflamed lymph nodes

The spatiotemporal regulation of immune cells in lymph nodes (LNs) is crucial for mounting protective T-cell responses, which are orchestrated by dendritic cells (DCs). However, it is unclear how the DC subsets are altered by the inflammatory milieu of LNs. Here, we show that the inflamed LNs of Listeria-infected mice are characterized by the clustering of neutrophils and monocytes and IFN-γ production. Significantly, the early inflammatory responses are coupled with the differentiation of not one, but two types of CD64⁺CD11c⁺MHCII⁺ inflammatory DCs. Through the assessment of chemokine receptor dependency, gene expression profiles, growth factor requirements and DC-specific lineage mapping, we herein unveil a novel inflammatory DC population (we termed ‘CD64⁺ cDCs’) that arises from conventional DCs (cDCs), distinguishable from CD64⁺ monocyte-derived DCs (moDCs) in inflamed LNs. We determined that Listeria-induced type I IFN is a critical inflammatory cue for the development of CD64⁺ cDCs but not CD64⁺ moDCs. Importantly, CD64⁺ cDCs displayed a higher potential to activate T cells than CD64⁺ moDCs, whereas the latter showed more robust expression of inflammatory genes. Although CD64⁺ and CD64− cDCs were able to cross-present soluble antigens at a high dose to CD8⁺ T cells, CD64⁺ cDCs concentrated and cross-presented a minute amount of soluble antigens delivered via CD64 (FcγRI) as immune complexes. These findings reveal the role of early inflammatory responses in driving the differentiation of two inflammatory DC subsets empowered with distinct competencies.

Mutation Analysis of Synthetic DNA Barcodes in a Fission Yeast Gene Deletion Library by Sanger Sequencing

Incorporation of unique barcodes into fission yeast gene deletion collections has enabled the identification of gene functions by growth fitness analysis. For fine tuning, it is important to examine barcode sequences, because mutations arise during strain construction. Out of 8,708 barcodes (4,354 strains) covering 88.5% of all 4,919 open reading frames, 7,734 barcodes (88.8%) were validated as high-fidelity to be inserted at the correct positions by Sanger sequencing. Sequence examination of the 7,734 high-fidelity barcodes revealed that 1,039 barcodes (13.4%) deviated from the original design. In total, 1,284 mutations (mutation rate of 16.6%) exist within the 1,039 mutated barcodes, which is comparable to budding yeast (18%). When the type of mutation was considered, substitutions accounted for 845 mutations (10.9%), deletions accounted for 319 mutations (4.1%), and insertions accounted for 121 mutations (1.6%). Peculiarly, the frequency of substitutions (67.6%) was unexpectedly higher than in budding yeast (~28%) and well above the predicted error of Sanger sequencing (~2%), which might have arisen during the solid-phase oligonucleotide synthesis and PCR amplification of the barcodes during strain construction. When the mutation rate was analyzed by position within 20-mer barcodes using the 1,284 mutations from the 7,734 sequenced barcodes, there was no significant difference between up-tags and down-tags at a given position. The mutation frequency at a given position was similar at most positions, ranging from 0.4% (32/7,734) to 1.1% (82/7,734), except at position 1, which was highest (3.1%), as in budding yeast. Together, well-defined barcode sequences, combined with the next-generation sequencing platform, promise to make the fission yeast gene deletion library a powerful tool for understanding gene function.